Note: Clicking on the option with a triangle bullet ▸ next to it will expand/collapse its detailed information.; Type name written in PascalCase typically refer to a NEML2 object type, oftentimes a primitive tensor type.; The 🔗 symbol means that the tensor value can be cross-reference another object. See Model parameters (revisited) for details.; You can always use Ctrl+F or Cmd+F to search the entire page.

The following symbols are used throughout the documentation to denote different components of function definition.

🇮: input variable
🇴: output variable
🇵: parameter
🇧: buffer

Available objects and their input file syntax

Refer to System Documentation for detailed explanation about this system.

AdvectiveStress

Calculate the advective stress, \( p_s \), taking the form of \( p_s = \frac{c}{3J} P_{ij}F_{ij} \). Here, \( J, P, F \) are the the deformation gradient Jacobian, the 1st Piola-Kirchhoff stress and the defomration gradient. \( c \) is the volume change coefficient.

advective_stress 🇴 The average advective stress

Type: string
Required: No
Default: advective_stress

coefficient 🇵 Coefficient c

Type: Scalar 🔗
Required: Yes

deformation_gradient 🇮 The deformation gradient

Type: string
Required: No
Default: deformation_gradient

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

js 🇮 The Jacobian of the deformation gradient associated with the swelling and phase change

Type: string
Required: No

jt 🇮 The Jacobian of the deformation gradient associated with the thermal and volume expansion

Type: string
Required: No

pk1_stress 🇮 1st Piola-Kirchhoff stress

Type: string
Required: No
Default: pk1_stress

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

ArrheniusParameter

Define the variable as a function of temperature according to the Arrhenius law \( p = p_0 \exp \left( -\frac{Q}{RT} \right) \), where \( p_0 \) is the reference value, \( Q \) is the activation energy, \( R \) is the ideal gas constant, and \( T \) is the temperature.

activation_energy 🇵 Activation energy

Type: Scalar 🔗
Required: Yes

ideal_gas_constant The ideal gas constant

Type: number
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not provided, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reference_value 🇵 Reference value

Type: Scalar 🔗
Required: Yes

temperature 🇮 Temperature

Type: string
Required: No
Default: temperature

Detailed documentation link

AssociativeIsotropicPlasticHardening

Map the flow rate (i.e., the consistency parameter in the KKT conditions) to the rate of internal variables. This object calculates the rate of equivalent plastic strain following associative flow rule, i.e. \( \dot{\bar{\varepsilon}}_p = - \dot{\gamma} \frac{\partial f}{\partial k} \), where \( \dot{\bar{\varepsilon}}_p \) is the equivalent plastic strain, \( \dot{\gamma} \) is the flow rate, \( f \) is the yield function, and \( k \) is the isotropic hardening.

equivalent_plastic_strain_rate 🇴 Rate of equivalent plastic strain

Type: string
Required: No
Default: equivalent_plastic_strain_rate

flow_rate 🇮 Flow rate

Type: string
Required: No
Default: flow_rate

isotropic_hardening_direction 🇮 Direction of associative isotropic hardening which can be calculated using Normality.

Type: string
Required: No
Default: isotropic_hardening_direction

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

AssociativeJ2FlowDirection

The plastic flow direction assuming an associative J2 flow.

flow_direction 🇴 Flow direction

Type: string
Required: No
Default: flow_direction

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

mandel_stress 🇮 Mandel stress

Type: string
Required: No
Default: mandel_stress

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

AssociativeKinematicPlasticHardening

Map the flow rate (i.e., the consistency parameter in the KKT conditions) to the rate of internal variables. This object calculates the rate of kinematic plastic strain following associative flow rule, i.e. \( \dot{\boldsymbol{K}}_p = - \dot{\gamma} \frac{\partial f}{\partial \boldsymbol{X}} \), where \( \dot{\boldsymbol{K}}_p \) is the kinematic plastic strain, \( \dot{\gamma} \) is the flow rate, \( f \) is the yield function, and \( \boldsymbol{X} \) is the kinematic hardening.

flow_rate 🇮 Flow rate

Type: string
Required: No
Default: flow_rate

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

kinematic_hardening_direction 🇮 Direction of associative kinematic hardening which can be calculated using Normality.

Type: string
Required: No
Default: kinematic_hardening_direction

kinematic_plastic_strain_rate 🇴 Rate of kinematic plastic strain

Type: string
Required: No
Default: kinematic_plastic_strain_rate

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

AssociativePlasticFlow

Map the flow rate (i.e., the consistency parameter in the KKT conditions) to the rate of internal variables. This object calculates the rate of plastic strain following associative flow rule, i.e. \( \dot{\boldsymbol{\varepsilon}}_p = - \dot{\gamma} \frac{\partial f}{\partial \boldsymbol{M}} \), where \( \dot{\boldsymbol{\varepsilon}}_p \) is the plastic strain, \( \dot{\gamma} \) is the flow rate, \( f \) is the yield function, and \( \boldsymbol{M} \) is the Mandel stress.

flow_direction 🇮 Flow direction which can be calculated using Normality

Type: string
Required: No
Default: flow_direction

flow_rate 🇮 Flow rate

Type: string
Required: No
Default: flow_rate

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

plastic_strain_rate 🇴 Rate of plastic strain

Type: string
Required: No
Default: plastic_strain_rate

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

AvramiErofeevNucleation

Avrami-Erofeev nucleation model, takes the form of \( f = k(1-a)(-ln(1-a))^n \), where \( k \) is the reaction coefficient, \( n \) is the reaction order, and \( a \) is the degree of conversion

coef 🇵 Reaction coefficient

Type: Scalar 🔗
Required: Yes

conversion_degree 🇮 Degree of conversion

Type: string
Required: No
Default: conversion_degree

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

order 🇵 Reaction order

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reaction_rate 🇴 Reaction rate

Type: string
Required: No
Default: reaction_rate

Detailed documentation link

BrooksCoreyCapillaryPressure

Relate the porous flow capillary pressure to the effective saturation using the Brooks Corey correlation taking the form of \( P_c = P_t S_e^{-\frac{1}{p}} \). Here \( S_e \) is the effective saturation, \( P_t \) is the threshold pressure at zero saturation, and \( p \) is the shape parameter

capillary_pressure 🇴 Capillary pressure.

Type: string
Required: No
Default: capillary_pressure

effective_saturation 🇮 The effective saturation

Type: string
Required: No
Default: effective_saturation

exponent 🇵 The shape parameter p

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

log_extension Whether to apply logarithmic extension

Type: bool
Required: No
Default: false

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

threshold_pressure 🇵 The threshold entry pressure

Type: Scalar 🔗
Required: Yes

transition_saturation The transition value of the effective saturation below which to apply the logarithmic extension

Type: number
Required: No

Detailed documentation link

ChabochePlasticHardening

Map the flow rate (i.e., the consistency parameter in the KKT conditions) to the rate of internal variables. This object defines the non-associative Fredrick-Armstrong kinematic hardening. In the model, back stress is directly treated as an internal variable. Rate of back stress is given as \( \dot{\boldsymbol{X}} = \left( \frac{2}{3} C \frac{\partial f}{\partial \boldsymbol{M}} - g \boldsymbol{X} \right) \dot{\gamma} \). \( \frac{\partial f}{\partial \boldsymbol{M}} \) is the flow direction, \( \dot{\gamma} \) is the flow rate, and \( C \) and \( g \) are material parameters. The complete Chaboche model adds static recovery terms \( - A \lVert \boldsymbol{X} \rVert^{a - 1} \boldsymbol{X} \), so the model includes kinematic hardening, dynamic recovery, and static recovery. \( A \) and \( a \) are additional material parameters.

A 🇵 Static recovery prefactor

Type: Scalar 🔗
Required: Yes

C 🇵 Kinematic hardening coefficient

Type: Scalar 🔗
Required: Yes

a 🇵 Static recovery exponent

Type: Scalar 🔗
Required: Yes

back_stress 🇮 Back stress

Type: string
Required: No
Default: back_stress

flow_direction 🇮 Flow direction

Type: string
Required: No
Default: flow_direction

flow_rate 🇮 Flow rate

Type: string
Required: No
Default: flow_rate

g 🇵 Dynamic recovery coefficient

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

ComposedModel

Compose multiple models together to form a single model. The composed model can then be treated as a new model and composed with others. The system documentation provides in-depth explanation on how the models are composed together.

additional_outputs Extra output variables to be extracted from the composed model in addition to the ones identified through dependency resolution.

Type: list of string
Required: No

automatic_nonlinear_parameter Whether to automatically add dependent nonlinear parameters

Type: bool
Required: No
Default: true

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

models Models being composed together

Type: list of string
Required: Yes

priority Priorities of models in decreasing order. A model with higher priority will be evaluated first. This is useful for breaking cyclic dependency.

Type: list of string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

ConstantExtrapolationPredictor

Use constant extrapolation as the initial guess for the unknowns at the current time step.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

unknowns_MillerIndex The unknowns to extrapolate of type MillerIndex

Type: list of string
Required: No

unknowns_Quaternion The unknowns to extrapolate of type Quaternion

Type: list of string
Required: No

unknowns_R2 The unknowns to extrapolate of type R2

Type: list of string
Required: No

unknowns_R3 The unknowns to extrapolate of type R3

Type: list of string
Required: No

unknowns_R4 The unknowns to extrapolate of type R4

Type: list of string
Required: No

unknowns_Rot The unknowns to extrapolate of type Rot

Type: list of string
Required: No

unknowns_SFFR4 The unknowns to extrapolate of type SFFR4

Type: list of string
Required: No

unknowns_SFR3 The unknowns to extrapolate of type SFR3

Type: list of string
Required: No

unknowns_SR2 The unknowns to extrapolate of type SR2

Type: list of string
Required: No

unknowns_SSR4 The unknowns to extrapolate of type SSR4

Type: list of string
Required: No

unknowns_SWR4 The unknowns to extrapolate of type SWR4

Type: list of string
Required: No

unknowns_Scalar The unknowns to extrapolate of type Scalar

Type: list of string
Required: No

unknowns_Vec The unknowns to extrapolate of type Vec

Type: list of string
Required: No

unknowns_WFFR4 The unknowns to extrapolate of type WFFR4

Type: list of string
Required: No

unknowns_WR2 The unknowns to extrapolate of type WR2

Type: list of string
Required: No

unknowns_WSR4 The unknowns to extrapolate of type WSR4

Type: list of string
Required: No

unknowns_WWR4 The unknowns to extrapolate of type WWR4

Type: list of string
Required: No

Detailed documentation link

ContractingGeometry

The contracting geometry model, often encountered in non-isothermal decomposition or solid-gas reactions, takes the form of \( f = k(1-a)^n \), where \( k \) is the reaction coefficient (often temperature-dependent), \( n \) is the reaction order, and \( a \) is the degree of conversion.

coef 🇵 Reaction coefficient, k

Type: Scalar 🔗
Required: Yes

conversion_degree 🇮 Degree of conversion

Type: string
Required: No
Default: conversion_degree

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

order 🇵 Reaction order, n

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reaction_rate 🇴 Reaction rate

Type: string
Required: No
Default: reaction_rate

Detailed documentation link

CopyMillerIndex

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyQuaternion

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyR2

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyR3

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyR4

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyRot

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopySFFR4

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopySFR3

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopySR2

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopySSR4

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopySWR4

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyScalar

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyVec

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyWFFR4

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyWR2

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyWSR4

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CopyWWR4

Copy the value from one variable to another.

from 🇮 Variable to copy value from

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 Variable to copy value to

Type: string
Required: No
Default: to

Detailed documentation link

CrackGeometricFunctionAT1

Crack geometric function associated with the AT-1 functional, \( \alpha = d \)

crack 🇴 Value of the crack geometric function

Type: string
Required: No
Default: crack

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

phase 🇮 Phase-field variable

Type: string
Required: No
Default: phase

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

CrackGeometricFunctionAT2

Crack geometric function associated with the AT-2 functional, \( \alpha = d^2 \)

crack 🇴 Value of the crack geometric function

Type: string
Required: No
Default: crack

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

phase 🇮 Phase-field variable

Type: string
Required: No
Default: phase

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

CrystalPlasticityStrainPredictor

Warm-up predictor for crystal plasticity models. Computes an initial guess for the elastic strain as \( \varepsilon^e = s \cdot \Delta t \cdot d \) where \( \Delta t = t - t_n \) is the time increment, \( d \) is the deformation rate, and \( s \) is a scale factor.

deformation_rate 🇮 Deformation rate tensor

Type: string
Required: No
Default: deformation_rate

elastic_strain 🇴 Elastic strain initial guess

Type: string
Required: No
Default: elastic_strain

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

scale 🇧 Scale factor applied to the strain increment

Type: Scalar 🔗
Required: Yes

threshold 🇧 Only apply the predictor if the old elastic strain norm is below this threshold. When the old elastic strain norm is above this threshold, fall back to use the old elastic strain as the initial guess for the nonlinear solve.

Type: Scalar 🔗
Required: No
Default: 1e-3

time 🇮 Current time

Type: string
Required: No
Default: t

Detailed documentation link

CubicElasticityTensor

This class defines a cubic anisotropic elasticity tensor using three parameters. Various options are available for which three parameters to provide.

coefficient_as_parameter Whether to treat the coefficients as (trainable) parameters. Default is true. Setting this option to false will treat the coefficients as buffers.

Type: list of bool
Required: No
Default: 1

coefficient_types Types for each parameter, options are: INVALID, P_WAVE_MODULUS, POISSONS_RATIO, YOUNGS_MODULUS, SHEAR_MODULUS, BULK_MODULUS, LAME_LAMBDA

Type: MultiEnumSelection
Required: No
Default: (INVALID)

coefficients 🇵 Coefficients used to define the elasticity tensor

Type: list of Scalar> 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

CylindricalChannelGeometry

Calculate the dimensionless inner and outer radii of the reaction product

inner_radius 🇴 Dimensionless inner radius of the product phase

Type: string
Required: No
Default: inner_radius

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

outer_radius 🇴 Dimensionless outer radius of the product phase

Type: string
Required: No
Default: outer_radius

product_fraction 🇮 Volume fraction of the product phase

Type: string
Required: No
Default: product_fraction

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

solid_fraction 🇮 Volume fraction of the solid phase

Type: string
Required: No
Default: solid_fraction

Detailed documentation link

DiffusionLimitedReaction

Calculate the void fraction rate of change

diffusion_coefficient 🇵 Diffusion coefficient of the rate-limiting species in the product phase

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

liquid_reactivity 🇮 Reactivity of the liquid phase, between 0 and 1

Type: string
Required: No
Default: liquid_reactivity

molar_volume Molar volume of the rate-limiting (liquid) species

Type: number
Required: Yes

product_dummy_thickness Minimum product thickness to avoid division by 0

Type: number
Required: No
Default: 0.01

product_inner_radius 🇮 Inner radius of the product phase

Type: string
Required: No
Default: product_inner_radius

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reaction_rate 🇴 Product phase substance volumetric rate of change

Type: string
Required: No
Default: reaction_rate

solid_inner_radius 🇮 Inner radius of the solid phase

Type: string
Required: No
Default: solid_inner_radius

solid_reactivity 🇮 Reactivity of the solid phase, between 0 and 1

Type: string
Required: No
Default: solid_reactivity

Detailed documentation link

DislocationObstacleStrengthMap

Dislocation density to strength as in Taylor \( \tau_i = \tau_{const} + \alpha \mu b \sqrt{\rho_i} \).

alpha 🇵 Interaction coefficient

Type: Scalar 🔗
Required: Yes

b 🇵 Burgers vector

Type: Scalar 🔗
Required: Yes

constant_strength 🇵 Constant strength offset

Type: Scalar 🔗
Required: Yes

dislocation_density 🇮 Per-slip dislocation density

Type: string
Required: No
Default: dislocation_density

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

mu 🇵 Shear modulus

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

slip_strengths 🇴 Name of the slip system strengths

Type: string
Required: No
Default: slip_strengths

Detailed documentation link

EffectiveSaturation

Calculate the effective saturation, taking the form of \( S = \frac{\frac{\phi}{\phi_\mathrm{max}} - S_r}{1-S_r} \) where \( \phi \) is the volume fraction of the flowing fluid, \( \phi_\mathrm{max} \) is the maximum allowable volume fraction and \( S_r \) is the residual saturation.

effective_saturation 🇴 Effective saturation

Type: string
Required: No
Default: effective_saturation

fluid_fraction 🇮 Volume fraction of the fluid

Type: string
Required: No
Default: fluid_fraction

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

max_fraction 🇵 Maximum allowable volume fraction of the fluid

Type: Scalar 🔗
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

residual_saturation 🇵 Liquid's residual volume fraction

Type: Scalar 🔗
Required: No

Detailed documentation link

EffectiveVolume

Calculate the total volume of a control mass. The volume has the form of \( V = \dfrac{M}{1-\phi_{o}} \sum_i \frac{\omega_i}{\rho_i} \), where \( \omega_i \) and \( \rho_i \) are respectively the mass fraction and the density of each component; \( \phi_{o} \) is the volume fraction accounting for leakage from the control mass; \( M \) is the reference mass of the composite.

composite_volume 🇴 Volume of the composite

Type: string
Required: No
Default: composite_volume

densities 🇵 Densities of the components in the composite

Type: list of Scalar> 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

mass_fractions 🇮 Mass fractions of the components in the composite

Type: list of string
Required: Yes

open_volume_fraction 🇮 Open volume fraction accounting for leakage

Type: string
Required: No
Default: open_volume_fraction

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reference_mass 🇵 Reference mass of the composite

Type: Scalar 🔗
Required: Yes

Detailed documentation link

ElasticStrainRate

Calculates the elastic strain rate as \(\dot{\varepsilon} = d - d^p - \varepsilon w + w \varepsilon \) where \( d \) is the deformation rate, \( d^p \) is the plastic deformation rate, \( w \) is the vorticity, and \( \varepsilon \) is the elastic strain.

deformation_rate 🇮 Name of the deformation rate

Type: string
Required: No
Default: deformation_rate

elastic_strain 🇮 Name of the elastic strain

Type: string
Required: No
Default: elastic_strain

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

plastic_deformation_rate 🇮 Name of the plastic deformation rate

Type: string
Required: No
Default: plastic_deformation_rate

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

vorticity 🇮 Name of the vorticity

Type: string
Required: No
Default: vorticity

Detailed documentation link

ExponentialLawPermeability

Define the relationship between non-dimensionalized porosity and permeability. The exponential porosity-permeability relation takes the form of \( K_0 \exp \left[ a(\varphi_o-\varphi) \right] \) where \( a \) is the scaling parameter; \( \varphi_0 \) and \( K_0 \) are the reference porosity and permeability respectively.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

permeability 🇴 The porosity-dependent permeability

Type: string
Required: No
Default: permeability

porosity 🇮 The porosity

Type: string
Required: No
Default: porosity

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reference_permeability 🇵 The reference permeability

Type: Scalar 🔗
Required: Yes

reference_porosity 🇵 The reference porosity

Type: Scalar 🔗
Required: Yes

scale 🇵 Scaling constant in the exponential law

Type: Scalar 🔗
Required: Yes

Detailed documentation link

FBComplementarity

If \( a \ge 0, b \ge 0, ab = 0 \) then the Fischer Burmeister (FB) complementarity condition is: \( r = a+b-\sqrt(a^2+b^2) = 0 \).

a 🇮 First condition

Type: string
Required: No
Default: a

a_inequality Type of the inequality for the first variable a.

Type: EnumSelection
Required: No
Default: GE

b 🇮 Second condition

Type: string
Required: No
Default: b

b_inequality Type of inequality for the second variable b.

Type: EnumSelection
Required: No
Default: GE

complementarity 🇴 The Fischer Burmeister complementarity condition

Type: string
Required: No
Default: complementarity

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

FiniteVolumeAppendBoundaryCondition

Append a boundary condition value to the intermediate dimension.

bc_value 🇵 Boundary condition value to append.

Type: Scalar 🔗
Required: Yes

input 🇮 Input tensor to append the boundary condition to.

Type: string
Required: No
Default: input

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

output 🇴 Output tensor name. Defaults to input + '_with_bc_left' or '_with_bc_right'.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

side Which side to append the boundary condition value to. Options are: right, left

Type: EnumSelection
Required: No
Default: left

Detailed documentation link

FiniteVolumeGradient

Compute prefactor-weighted gradients at cell edges using first-order reconstruction.

dx 🇵 Cell center spacing between adjacent cells.

Type: Scalar 🔗
Required: Yes

grad_u 🇴 Cell-edge prefactor-weighted gradients.

Type: string
Required: No
Default: grad_u

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

prefactor 🇵 Cell-edge prefactor values (defaults to 1).

Type: Scalar 🔗
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

u 🇮 Cell-averaged field values.

Type: string
Required: No
Default: u

Detailed documentation link

FiniteVolumeUpwindedAdvectiveFlux

Compute upwinded advective fluxes at cell edges.

flux 🇴 Cell-edge advective fluxes.

Type: string
Required: No
Default: flux

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

u 🇮 Cell-averaged field values.

Type: string
Required: No
Default: u

v_edge 🇮 Cell-edge advection velocity values.

Type: string
Required: No
Default: v_edge

Detailed documentation link

FixOrientation

Checks the value of the modified Rodrigues parameter by checking if \( \left\lVert r \right\rVert > t \), with \( t \) a threshold value set to 1.0 by default and replacing all the orientations that exceed this limit with their shadow parameters values.

input 🇮 Name of input tensor of orientations to operate on.

Type: string
Required: No
Default: input

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

output 🇴 Name of output tensor

Type: string
Required: No
Default: output

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

threshold Threshold value for translating to the shadow parameters

Type: number
Required: No
Default: 1

Detailed documentation link

FredrickArmstrongPlasticHardening

Map the flow rate (i.e., the consistency parameter in the KKT conditions) to the rate of internal variables. This object defines the non-associative Fredrick-Armstrong kinematic hardening. In the model, back stress is directly treated as an internal variable. Rate of back stress is given as \( \dot{\boldsymbol{X}} = \left( \frac{2}{3} C \frac{\partial f}{\partial \boldsymbol{M}} - g \boldsymbol{X} \right) \dot{\gamma} \). \( \frac{\partial f}{\partial \boldsymbol{M}} \) is the flow direction, \( \dot{\gamma} \) is the flow rate, and \( C \) and \( g \) are material parameters.

C 🇵 Kinematic hardening coefficient

Type: Scalar 🔗
Required: Yes

back_stress 🇮 Back stress

Type: string
Required: No
Default: back_stress

flow_direction 🇮 Flow direction

Type: string
Required: No
Default: flow_direction

flow_rate 🇮 Flow rate

Type: string
Required: No
Default: flow_rate

g 🇵 Dynamic recovery coefficient

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

GTNYieldFunction

Gurson-Tvergaard-Needleman yield function for poroplasticity. The yield function is defined as \( f = \left( \frac{\bar{\sigma}}{\sigma_y + k} \right)^2 + 2 q_1 \phi \cosh \left( \frac{1}{2} q_2 \frac{3\sigma_h-\sigma_s}{\sigma_y + k} \right) - \left( q_3 \phi^2 + 1 \right) \), where \( \bar{\sigma} \) is the von Mises stress, \( \sigma_y \) is the yield stress, \( k \) is isotropic hardening, \( \phi \) is the porosity, \( \sigma_h \) is the hydrostatic stress, and \( \sigma_s \) is the void growth back stress (sintering stress). \( q_1 \), \( q_2 \), and \( q_3 \) are parameters controlling the yield mechanisms.

flow_invariant 🇮 Effective stress driving plastic flow

Type: string
Required: No
Default: flow_invariant

isotropic_hardening 🇮 Isotropic hardening

Type: string
Required: No

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

poro_invariant 🇮 Effective stress driving porous flow

Type: string
Required: No
Default: poro_invariant

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

q1 🇵 Parameter controlling the balance/competition between plastic flow and void evolution.

Type: Scalar 🔗
Required: Yes

q2 🇵 Void evolution rate

Type: Scalar 🔗
Required: Yes

q3 🇵 Pore pressure

Type: Scalar 🔗
Required: Yes

void_fraction 🇮 Void fraction (porosity)

Type: string
Required: No
Default: void_fraction

yield_function 🇴 Yield function

Type: string
Required: No
Default: yield_function

yield_stress 🇵 Yield stress

Type: Scalar 🔗
Required: Yes

Detailed documentation link

GeneralElasticity

Relates elastic strain to stress with some non-isotropic tensor. This verion implements a general relation using the elasticity tensor, expressed as an SSR4 object

compliance Whether the model defines the compliance relationship, i.e., mapping from stress to elastic strain. When set to false (default), the model maps elastic strain to stress.

Type: bool
Required: No
Default: false

elastic_stiffness_tensor 🇵 Elastic stiffness tensor

Type: SSR4 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

orientation 🇮 Active convention orientation from reference to current

Type: string
Required: No
Default: orientation

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate_form Whether the model defines the stress-strain relationship in rate form. When set to true, the model maps elastic strain rate to stress rate.

Type: bool
Required: No
Default: false

strain 🇮 Elastic strain

Type: string
Required: No
Default: strain

stress 🇴 Stress

Type: string
Required: No
Default: stress

Detailed documentation link

GreenLagrangeStrain

Green-Lagrange strain, \( E = \frac{1}{2} (C - I) \), where \( C = F^T F \) is the right Cauchy-Green tensor and \( I \) is the identity tensor.

deformation_gradient 🇮 The deformation gradient

Type: string
Required: No
Default: deformation_gradient

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

strain 🇴 The Green-Lagrange strain

Type: string
Required: No
Default: strain

Detailed documentation link

GursonCavitation

Local mass balance used in conjunction with the GTNYieldFunction, \( \dot{\phi} = (1-\phi) \dot{\varepsilon}_p \).

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

plastic_strain_rate 🇮 Plastic strain rate

Type: string
Required: No
Default: plastic_strain_rate

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

void_fraction 🇮 Void fraction (porosity)

Type: string
Required: No
Default: void_fraction

void_fraction_rate 🇴 Rate of void evolution

Type: string
Required: No
Default: void_fraction_rate

Detailed documentation link

HermiteSmoothStep

The smooth step function defined by Hermite polynomials

argument 🇮 Argument of the smooth step function

Type: string
Required: No
Default: argument

complement Whether to take the complement of the smooth step function, i.e. 1 - smooth_step

Type: bool
Required: No
Default: false

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

lower_bound 🇧 Lower bound of the argument

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

upper_bound 🇧 Upper bound of the argument

Type: Scalar 🔗
Required: Yes

value 🇴 Value of the smooth step function

Type: string
Required: No
Default: value

Detailed documentation link

ImplicitUpdate

Update an implicit model by solving the underlying nonlinear system of equations.

equation_system The nonlinear system of equations to solve

Type: string
Required: Yes

predictor An optional predictor to provide an initial guess for the nonlinear solve.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

solver Solver used to solve the nonlinear system of equations

Type: string
Required: Yes

Detailed documentation link

IsotropicElasticityTensor

This class defines an isotropic elasticity tensor using two parameters. Various options are available for which two parameters to provide.

coefficient_as_parameter Whether to treat the coefficients as (trainable) parameters. Default is true. Setting this option to false will treat the coefficients as buffers.

Type: list of bool
Required: No
Default: 1

coefficient_types Types for each parameter, options are: INVALID, P_WAVE_MODULUS, POISSONS_RATIO, YOUNGS_MODULUS, SHEAR_MODULUS, BULK_MODULUS, LAME_LAMBDA

Type: MultiEnumSelection
Required: No
Default: (INVALID)

coefficients 🇵 Coefficients used to define the elasticity tensor

Type: list of Scalar> 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

IsotropicMandelStress

Map Cauchy stress to Mandel stress For isotropic material under small deformation, the Mandel stress and the Cauchy stress coincide.

cauchy_stress 🇮 Cauchy stress

Type: string
Required: No
Default: cauchy_stress

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

mandel_stress 🇴 Mandel stress

Type: string
Required: No
Default: mandel_stress

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

KocksMeckingActivationEnergy

Calculates the Kocks-Mecking normalized activation as \(g = \frac{kT}{\mu b^3} \log \frac{\dot{\varepsilon}_0}{\dot{\varepsilon}} \) with \( \mu \) the shear modulus, \( k \) the Boltzmann constant, \( T \) the absolute temperature, \( b \) the Burgers vector length, \( \dot{\varepsilon}_0 \) a reference strain rate, and \( \dot{\varepsilon} \) the current strain rate.

activation_energy 🇴 Output name of the activation energy

Type: string
Required: No
Default: activation_energy

b Magnitude of the Burgers vector

Type: number
Required: Yes

eps0 Reference strain rate

Type: number
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

k The Boltzmann constant

Type: number
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

shear_modulus 🇵 The shear modulus

Type: Scalar 🔗
Required: Yes

strain_rate 🇮 Effective strain rate

Type: string
Required: No
Default: strain_rate

temperature 🇮 Absolute temperature

Type: string
Required: No
Default: temperature

Detailed documentation link

KocksMeckingFlowSwitch

Switches between rate independent and rate dependent flow rules based on the value of the Kocks-Mecking normalized activation energy. For activation energies less than the threshold use the rate independent flow rule, for values greater than the threshold use the rate dependent flow rule. This version uses a soft switch between the models, based on a tanh sigmoid function.

activation_energy 🇮 The input name of the activation energy

Type: string
Required: No
Default: activation_energy

flow_rate 🇴 Output name for the mixed flow rate

Type: string
Required: No
Default: flow_rate

g0 🇵 Critical value of activation energy

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate_dependent_flow_rate 🇮 Input name of the rate dependent flow rate

Type: string
Required: No
Default: rate_dependent_flow_rate

rate_independent_flow_rate 🇮 Input name of the rate independent flow rate

Type: string
Required: No
Default: rate_independent_flow_rate

sharpness A steepness parameter that controls the tanh mixing of the models. Higher values gives a sharper transition.

Type: number
Required: No
Default: 1

Detailed documentation link

KocksMeckingFlowViscosity

Calculates the temperature-dependent flow viscosity for a Perzyna-type model using the Kocks-Mecking model. The value is \( \eta = \exp{B} \mu \dot{\varepsilon}_0^\frac{-k T A}{\mu b^3} \) with \( \mu \) the shear modulus, \( \dot{\varepsilon}_0 \) a reference strain rate, \( b \) the Burgers vector, \( k\) the Boltzmann constant, \( T \) absolute temperature, \( A \) the Kocks-Mecking slope parameter, and \( B \) the Kocks-Mecking intercept parameter.

A 🇵 The Kocks-Mecking slope parameter

Type: Scalar 🔗
Required: Yes

B 🇵 The Kocks-Mecking intercept parameter

Type: Scalar 🔗
Required: Yes

b The Burgers vector

Type: number
Required: Yes

eps0 The reference strain rate

Type: number
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

k Boltzmann constant

Type: number
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

shear_modulus 🇵 The shear modulus

Type: Scalar 🔗
Required: Yes

temperature 🇮 Absolute temperature

Type: string
Required: No
Default: temperature

Detailed documentation link

KocksMeckingIntercept

The critical value of the normalized activation energy given by \( g_0 \frac{C-B}{A} \)

A 🇵 The Kocks-Mecking slope

Type: Scalar 🔗
Required: Yes

B 🇵 The Kocks-Mecking intercept

Type: Scalar 🔗
Required: Yes

C 🇵 The Kocks-Mecking horizontal value

Type: Scalar 🔗
Required: Yes

intercept 🇴 The intercept

Type: string
Required: No
Default: intercept

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

KocksMeckingRateSensitivity

Calculates the temperature-dependent rate sensitivity for a Perzyna-type model using the Kocks-Mecking model. The value is \( n = \frac{\mu b^3}{k T A} \) with \( \mu \) the shear modulus, \( b \) the Burgers vector, \( k\) the Boltzmann constant, \( T \) absolute temperature, and \( A \) the Kocks-Mecking slope parameter.

A 🇵 The Kocks-Mecking slope parameter

Type: Scalar 🔗
Required: Yes

b The Burgers vector

Type: number
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

k Boltzmann constant

Type: number
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate_sensitivity 🇴 Output name of the rate sensitivity

Type: string
Required: No
Default: rate_sensitivity

shear_modulus 🇵 The shear modulus

Type: Scalar 🔗
Required: Yes

temperature 🇮 Absolute temperature

Type: string
Required: No
Default: temperature

Detailed documentation link

KocksMeckingYieldStress

The yield stress given by the Kocks-Mecking model. \( \sigma_y = \exp{C} \mu \) with \( \mu \) the shear modulus and \( C \) the horizontal intercept from the Kocks-Mecking diagram.

C 🇵 The Kocks-Mecking horizontal intercept

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

shear_modulus 🇵 The shear modulus

Type: Scalar 🔗
Required: Yes

yield_stress 🇴 Output name of the yield stress

Type: string
Required: No
Default: yield_stress

Detailed documentation link

KozenyCarmanPermeability

Define the relationship between non-dimensionalized porosity and permeability. The Kozeny-Carman porosity-permeability relation takes the form of \( K = K_0 \frac{\varphi^n (1-\varphi_0^m)}{\varphi_0^m (1-\varphi)^n} \) where \( n \) and \( m \) are shape parameters. \( varphi_0 \) and \( K_0 \) are the reference porosity and permeability respectively.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

m 🇵 Shape parameter m

Type: Scalar 🔗
Required: Yes

n 🇵 Shape parameter n

Type: Scalar 🔗
Required: Yes

permeability 🇴 The porosity-dependent permeability

Type: string
Required: No
Default: permeability

porosity 🇮 The porosity

Type: string
Required: No
Default: porosity

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reference_permeability 🇵 the reference permeability

Type: Scalar 🔗
Required: Yes

reference_porosity 🇵 the reference porosity

Type: Scalar 🔗
Required: Yes

Detailed documentation link

LinearExtrapolationPredictor

Use temporal extrapolation assuming constant rate of change as the initial guess for the unknowns at the current time step. The linear extrapolation can be written as \(u = u_n + (u_n - u_{n-1}) \frac{t - t_n}{t_n - t_{n-1}}\), where \(u\) is the unknown and \(n\) is the time step counter, respectively.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

time 🇮 Time

Type: string
Required: No
Default: t

unknowns_MillerIndex The unknowns to extrapolate of type MillerIndex

Type: list of string
Required: No

unknowns_Quaternion The unknowns to extrapolate of type Quaternion

Type: list of string
Required: No

unknowns_R2 The unknowns to extrapolate of type R2

Type: list of string
Required: No

unknowns_R3 The unknowns to extrapolate of type R3

Type: list of string
Required: No

unknowns_R4 The unknowns to extrapolate of type R4

Type: list of string
Required: No

unknowns_Rot The unknowns to extrapolate of type Rot

Type: list of string
Required: No

unknowns_SFFR4 The unknowns to extrapolate of type SFFR4

Type: list of string
Required: No

unknowns_SFR3 The unknowns to extrapolate of type SFR3

Type: list of string
Required: No

unknowns_SR2 The unknowns to extrapolate of type SR2

Type: list of string
Required: No

unknowns_SSR4 The unknowns to extrapolate of type SSR4

Type: list of string
Required: No

unknowns_SWR4 The unknowns to extrapolate of type SWR4

Type: list of string
Required: No

unknowns_Scalar The unknowns to extrapolate of type Scalar

Type: list of string
Required: No

unknowns_Vec The unknowns to extrapolate of type Vec

Type: list of string
Required: No

unknowns_WFFR4 The unknowns to extrapolate of type WFFR4

Type: list of string
Required: No

unknowns_WR2 The unknowns to extrapolate of type WR2

Type: list of string
Required: No

unknowns_WSR4 The unknowns to extrapolate of type WSR4

Type: list of string
Required: No

unknowns_WWR4 The unknowns to extrapolate of type WWR4

Type: list of string
Required: No

Detailed documentation link

LinearIsotropicElasticJ2TrialStressUpdate

Update the trial stress under the assumptions of J2 plasticity and isotropic linear elasticity

coefficient_as_parameter Whether to treat the coefficients as (trainable) parameters. Default is true. Setting this option to false will treat the coefficients as buffers.

Type: list of bool
Required: No
Default: 1

coefficient_types Types for each parameter, options are: INVALID, P_WAVE_MODULUS, POISSONS_RATIO, YOUNGS_MODULUS, SHEAR_MODULUS, BULK_MODULUS, LAME_LAMBDA

Type: MultiEnumSelection
Required: No
Default: (INVALID)

coefficients 🇵 Coefficients used to define the elasticity tensor

Type: list of Scalar> 🔗
Required: Yes

elastic_trial_stress 🇮 Initial trial stress assuming a purely elastic step

Type: string
Required: No
Default: elastic_trial_stress

equivalent_plastic_strain 🇮 Current guess for the equivalent plastic strain

Type: string
Required: No
Default: equivalent_plastic_strain

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

updated_trial_stress 🇴 Trial stress corrected for the current increment of plastic deformation

Type: string
Required: No
Default: updated_trial_stress

Detailed documentation link

LinearIsotropicElasticity

Relate elastic strain to stress for linear isotropic material. \( \boldsymbol{\sigma} = K \tr \boldsymbol{\varepsilon}_e + 2 G \text{dev} \boldsymbol{\varepsilon}_e \), where \( K \) and \( G \) are bulk and shear moduli, respectively. Other pairs of Lame parameters are also supported.

coefficient_as_parameter Whether to treat the coefficients as (trainable) parameters. Default is true. Setting this option to false will treat the coefficients as buffers.

Type: list of bool
Required: No
Default: 1

coefficient_types Types for each parameter, options are: INVALID, P_WAVE_MODULUS, POISSONS_RATIO, YOUNGS_MODULUS, SHEAR_MODULUS, BULK_MODULUS, LAME_LAMBDA

Type: MultiEnumSelection
Required: No
Default: (INVALID)

coefficients 🇵 Coefficients used to define the elasticity tensor

Type: list of Scalar> 🔗
Required: Yes

compliance Whether the model defines the compliance relationship, i.e., mapping from stress to elastic strain. When set to false (default), the model maps elastic strain to stress.

Type: bool
Required: No
Default: false

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate_form Whether the model defines the stress-strain relationship in rate form. When set to true, the model maps elastic strain rate to stress rate.

Type: bool
Required: No
Default: false

strain 🇮 Elastic strain

Type: string
Required: No
Default: strain

stress 🇴 Stress

Type: string
Required: No
Default: stress

Detailed documentation link

LinearIsotropicHardening

Map equivalent plastic strain to isotropic hardening following a linear relationship, i.e., \( h = K \bar{\varepsilon}_p \) where \( K \) is the hardening modulus.

equivalent_plastic_strain 🇮 Equivalent plastic strain

Type: string
Required: No
Default: equivalent_plastic_strain

hardening_modulus 🇵 Hardening modulus

Type: Scalar 🔗
Required: Yes

isotropic_hardening 🇴 Isotropic hardening

Type: string
Required: No
Default: isotropic_hardening

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

LinearIsotropicStrainEnergyDensity

Calculates elastic strain energy density based on linear elastic isotropic response

active_strain_energy_density 🇴 Active part of the strain energy density

Type: string
Required: No
Default: active_strain_energy_density

coefficient_as_parameter Whether to treat the coefficients as (trainable) parameters. Default is true. Setting this option to false will treat the coefficients as buffers.

Type: list of bool
Required: No
Default: 1

coefficient_types Types for each parameter, options are: INVALID, P_WAVE_MODULUS, POISSONS_RATIO, YOUNGS_MODULUS, SHEAR_MODULUS, BULK_MODULUS, LAME_LAMBDA

Type: MultiEnumSelection
Required: No
Default: (INVALID)

coefficients 🇵 Coefficients used to define the elasticity tensor

Type: list of Scalar> 🔗
Required: Yes

decomposition Strain energy density decomposition types, options are: VOLDEV, SPECTRAL, NONE

Type: EnumSelection
Required: No
Default: NONE

inactive_strain_energy_density 🇴 Inactive part of the strain energy density

Type: string
Required: No
Default: inactive_strain_energy_density

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

strain 🇮 Elastic strain

Type: string
Required: No
Default: strain

Detailed documentation link

LinearKinematicHardening

Map kinematic plastic strain to back stress following a linear relationship, i.e., \( \boldsymbol{X} = H \boldsymbol{K}_p \) where \( H \) is the hardening modulus.

back_stress 🇴 Back stress

Type: string
Required: No
Default: back_stress

hardening_modulus 🇵 Hardening modulus

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

kinematic_plastic_strain 🇮 Kinematic plastic strain

Type: string
Required: No
Default: kinematic_plastic_strain

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

LinearSingleSlipHardeningRule

Simple linear slip system hardening defined by \( \dot{\tau} = \theta \sum_{i=1}^{n_{slip}} \left| \dot{\gamma}_i \right| \) where \( \theta \) is the hardening slope.

hardening_slope 🇵 Hardening rate

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

slip_hardening 🇮 Name of current values of slip hardening

Type: string
Required: No
Default: slip_hardening

sum_slip_rates 🇮 Name of tensor containing the sum of the slip rates

Type: string
Required: No
Default: sum_slip_rates

Detailed documentation link

LinearlyInterpolateToCellEdges

Linearly interpolate cell-centered values to cell edges using cell center and edge positions.

cell_centers 🇵 Cell center positions.

Type: Scalar 🔗
Required: Yes

cell_edges 🇵 Cell edge positions.

Type: Scalar 🔗
Required: Yes

cell_values 🇵 Cell-centered values to interpolate.

Type: Scalar 🔗
Required: Yes

edge_values 🇴 Linearly interpolated cell-edge values.

Type: string
Required: No
Default: edge_values

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

MillerIndexConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: MillerIndex 🔗
Required: Yes

Detailed documentation link

MillerIndexDynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

MillerIndexDynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

MillerIndexInputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

MillerIndexIntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

MillerIndexIntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

MillerIndexIntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

MillerIndexParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: MillerIndex 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

MixedControlSetup

'Mix' two variables \( \underline{x} \) and \( \bar{x} \) into a single output variable \( y \). For each component of the control signal, if the control is above the threshold, then the corresponding component of \( y \) is set to the corresponding component of \( \bar{x} \), otherwise it is set to the corresponding component of \( \underline{x} \). Values not selected by the control signal are output to \( z \).

control 🇮 The control signal.

Type: string
Required: No
Default: control

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

threshold 🇧 The threshold to switch between the two control

Type: SR2 🔗
Required: No
Default: 0.5

x_above 🇮 The variable whose values are selected when the control signal is greater than the threshold.

Type: string
Required: No
Default: x_above

x_below 🇮 The variable whose values are selected when the control signal is less than or equal to the threshold.

Type: string
Required: No
Default: x_below

y 🇴 The output variable holding the selected values based on the control signal.

Type: string
Required: No
Default: y

z 🇴 The output variable holding the non-selected values based on the control signal.

Type: string
Required: No
Default: z

Detailed documentation link

Normality

Store the first derivatives of a scalar-valued function in given variables, i.e. \( u_i = \dfrac{f(\boldsymbol{v})}{v_i} \).

from Function arguments to take derivatives w.r.t.

Type: list of string
Required: Yes

function Function to take derivative

Type: string
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

model The model which evaluates the scalar-valued function

Type: string
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to Variables to store the first derivatives

Type: list of string
Required: Yes

Detailed documentation link

OlevskySinteringStress

Define the Olevsky-Skorohod sintering stress to be used in conjunction with poroplasticity yield functions such as the GTNYieldFunction. The sintering stress is defined as \( \sigma_s = 3 \dfrac{\gamma}{r} \phi^2 \), where \( \gamma \) is the surface tension, \( r \) is the size of the particles/powders, and \( \phi \) is the void fraction.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

particle_radius 🇵 Particle radius

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

sintering_stress 🇴 Sintering stress

Type: string
Required: No
Default: sintering_stress

surface_tension 🇵 Surface tension

Type: Scalar 🔗
Required: Yes

void_fraction 🇮 Void fraction

Type: string
Required: No
Default: void_fraction

Detailed documentation link

OrientationRate

Defines the rate of the crystal orientations as a spin given by \( \Omega^e = w - w^p - \varepsilon d^p + d^p \varepsilon \) where \( \Omega^e = \dot{Q} Q^T \), \( Q \) is the orientation, \( w \) is the vorticity, \( w^p \) is the plastic vorticity, \( d^p \) is the plastic deformation rate, and \( \varepsilon \) is the elastic stretch.

elastic_strain 🇮 The name of the elastic strain tensor

Type: string
Required: No
Default: elastic_strain

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

orientation 🇮 The name of the orientation

Type: string
Required: No
Default: orientation

plastic_deformation_rate 🇮 The name of the plastic deformation rate

Type: string
Required: No
Default: plastic_deformation_rate

plastic_vorticity 🇮 The name of the plastic vorticity

Type: string
Required: No
Default: plastic_vorticity

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

vorticity 🇮 The name of the vorticity tensor

Type: string
Required: No
Default: vorticity

Detailed documentation link

PerSlipForestDislocationEvolution

Standard forest hardening model per slip system defined by \( \dot{\rho}_i = (k_1 \sqrt{\rho_i} - k_2 \rho_i) \left| \dot{\gamma}_i \right| \).

dislocation_density 🇮 Per-slip dislocation density

Type: string
Required: No
Default: dislocation_density

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

k1 🇵 Hardening coefficient

Type: Scalar 🔗
Required: Yes

k2 🇵 Recovery coefficient

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

slip_rates 🇮 Per-slip system slip rates

Type: string
Required: No
Default: slip_rates

Detailed documentation link

PerzynaPlasticFlowRate

Perzyna's viscous approximation of the consistent yield envelope (with a power law), i.e. \( \dot{\gamma} = \left( \frac{\left< f \right>}{\eta} \right)^n \), where \( f \) is the yield function, \( \eta \) is the reference stress, and \( n \) is the power-law exponent.

exponent 🇵 Power-law exponent

Type: Scalar 🔗
Required: Yes

flow_rate 🇴 Flow rate

Type: string
Required: No
Default: flow_rate

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reference_stress 🇵 Reference stress

Type: Scalar 🔗
Required: Yes

yield_function 🇮 Yield function

Type: string
Required: No
Default: yield_function

Detailed documentation link

PhaseTransformationEigenstrain

Define the (cummulative, as opposed to instantaneous) linear isotropic phase transformation (from phase A to phase B) eigenstrain, i.e. \( \boldsymbol{\varepsilon}_\mathrm{PT} = \Delta V f \boldsymbol{I} \), where \( \Delta V \) is the volume fraction change when going from phase A to B, \( f \) is the phase fraction (0 to 1, A to B).

eigenstrain 🇴 Eigenstrain

Type: string
Required: No
Default: eigenstrain

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

phase_fraction 🇮 Phase fraction

Type: string
Required: No
Default: phase_fraction

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

volume_fraction_change 🇮 Change in volume fraction going from phase A to phase B

Type: string
Required: No
Default: volume_fraction_change

Detailed documentation link

PlasticDeformationRate

Caclulates the plastic deformation rate as \( d^p = \sum_{i=1}^{n_{slip}} \dot{\gamma}_i Q \operatorname{sym}{\left(d_i \otimes n_i \right)} Q^T \) with \( d^p \) the plastic deformation rate, \( \dot{\gamma}_i \) the slip rate on the ith slip system, \(Q \) the orientation, \( d_i \) the slip system direction, and \( n_i \) the slip system normal.

crystal_geometry The name of the Data object containing the crystallographic information for the material

Type: string
Required: No
Default: crystal_geometry

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

orientation_matrix 🇮 The name of the orientation matrix

Type: string
Required: No
Default: orientation_matrix

plastic_deformation_rate 🇴 The name of the plastic deformation rate tensor

Type: string
Required: No
Default: plastic_deformation_rate

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

slip_rates 🇮 The name of the tensor containg the current slip rates

Type: string
Required: No
Default: slip_rates

Detailed documentation link

PlasticSpatialVelocityGradient

Caclulates the plastic spatial velocity gradient as \( l^p = \sum_{i=1}^{n_{slip}} \dot{\gamma}_i Q \left(d_i \otimes n_i \right) Q^T \) with \( l^p \) the plastic spatial velocity gradient, \( \dot{\gamma}_i \) the slip rate on the ith slip system, \(Q \) the orientation, \( d_i \) the slip system direction, and \( n_i \) the slip system normal.

crystal_geometry The name of the Data object containing the crystallographic information for the material

Type: string
Required: No
Default: crystal_geometry

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

orientation_matrix 🇮 The name of the orientation matrix

Type: string
Required: No
Default: orientation_matrix

plastic_spatial_velocity_gradient 🇴 The name of the plastic spatial velocity gradient

Type: string
Required: No
Default: plastic_spatial_velocity_gradient

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

slip_rates 🇮 The name of the tensor containg the current slip rates

Type: string
Required: No
Default: slip_rates

Detailed documentation link

PlasticVorticity

Caclulates the plastic vorcitity as \( w^p = \sum_{i=1}^{n_{slip}} \dot{\gamma}_i Q \operatorname{skew}{\left(d_i \otimes n_i \right)} Q^T \) with \( d^p \) the plastic deformation rate, \( \dot{\gamma}_i \) the slip rate on the ith slip system, \(Q \) the orientation, \( d_i \) the slip system direction, and \( n_i \) the slip system normal.

crystal_geometry The name of the Data object containing the crystallographic information for the material

Type: string
Required: No
Default: crystal_geometry

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

orientation_matrix 🇮 The name of the orientation matrix

Type: string
Required: No
Default: orientation_matrix

plastic_vorticity 🇴 The name of the plastic vorticity tensor

Type: string
Required: No
Default: plastic_vorticity

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

slip_rates 🇮 The name of the tensor containg the current slip rates

Type: string
Required: No
Default: slip_rates

Detailed documentation link

PowerDegradationFunction

Power degradation function to degrade the elastic strain energy density, \( g = \left( 1-d \right)^p (1-\eta) + \eta \)

degradation 🇴 Value of the degradation function

Type: string
Required: No
Default: degradation

eta Residual degradation when d = 1

Type: number
Required: No

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

phase 🇮 Phase-field variable

Type: string
Required: No
Default: phase

power Power of the degradation function

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

PowerLawIsotropicHardeningStaticRecovery

This particular model implements a power law recovery of the type \( \dot{k} = -\left(\frac{\lVert k \rVert}{\tau}\right)^{n-1} \frac{k}{\tau} \)

isotropic_hardening 🇮 Isotropic hardening variable

Type: string
Required: No
Default: isotropic_hardening

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n 🇵 Recovery exponent

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

tau 🇵 Recovery rate

Type: Scalar 🔗
Required: Yes

Detailed documentation link

PowerLawKinematicHardeningStaticRecovery

This object defines kinematic hardening static recovery on a backstress term. This particular model uses a power law for recovery \( \dot{X} = - \left(\frac{\lVert X \rVert}{\tau}\right)^{n-1} \frac{X}{\tau} \)where \( n \) is the power law recovery exponent and \(\tau\) is the recovery rate.

back_stress 🇮 Back stress

Type: string
Required: No
Default: back_stress

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n 🇵 Static recovery exponent

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

tau 🇵 Static recovery rate

Type: Scalar 🔗
Required: Yes

Detailed documentation link

PowerLawPermeability

Define the relationship between non-dimensionalized porosity and permeability. The power law porosity-permeability relation takes the form of \( K_0 \left( \frac{\varphi}{\varphi_0} \right)^p \). \( varphi_0 \) and \( K_0 \) are the reference porosity and permeability respectively.

exponent 🇵 The exponent in the power law

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

permeability 🇴 The porosity-dependent permeability

Type: string
Required: No
Default: permeability

porosity 🇮 The porosity

Type: string
Required: No
Default: porosity

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reference_permeability 🇵 The reference permeability

Type: Scalar 🔗
Required: Yes

reference_porosity 🇵 The reference porosity

Type: Scalar 🔗
Required: Yes

Detailed documentation link

PowerLawSlipRule

Power law slip rule defined as \( \dot{\gamma}_i = \dot{\gamma}_0 \left| \frac{\tau_i}{\hat{\tau}_i} \right|^{n-1} \frac{\tau_i}{\hat{\tau}_i} \) with \( \dot{\gamma}_i \) the slip rate on system \( i \), \( \tau_i \) the resolved shear, \( \hat{\tau}_i \) the slip system strength, \( n \) the rate senstivity, and \( \dot{\gamma}_0 \) a reference slip rate.

gamma0 🇵 Reference slip rate

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n 🇵 Rate sensitivity exponent

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

resolved_shears 🇮 Name of the resolved shear tensor

Type: string
Required: No
Default: resolved_shears

slip_rates 🇴 Name of the slip rate tensor

Type: string
Required: No
Default: slip_rates

slip_strengths 🇮 Name of the tensor containing the slip system strengths

Type: string
Required: No
Default: slip_strengths

Detailed documentation link

QuaternionConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: Quaternion 🔗
Required: Yes

Detailed documentation link

QuaternionDynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

QuaternionDynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

QuaternionInputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

QuaternionIntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

QuaternionIntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

QuaternionIntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

QuaternionParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: Quaternion 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

R2BackwardEulerTimeIntegration

Define the backward Euler time integration residual \( r = s - s_n - (t - t_n) \dot{s} \), where \(s\) is the variable being integrated, \(\dot{s}\) is the variable rate, and \(t\) is time. Subscripts \(n\) denote quantities from the previous time step.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate 🇮 Name of the variable rate.

Type: string
Required: No

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇮 Variable being integrated

Type: string
Required: No
Default: variable

Detailed documentation link

R2ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: R2 🔗
Required: Yes

Detailed documentation link

R2Determinant

Calculate the Jacobian of a second order tensor.

determinant 🇴 The determinant of the input tensor

Type: string
Required: No
Default: determinant

input 🇮 The second order tensor to calculate the determinant of

Type: string
Required: No
Default: input

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

R2DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R2DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R2InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

R2IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R2IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R2IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R2LinearCombination

Calculate linear combination of multiple R2 tensors as \( u = w_i v_i + b \) (Einstein summation assumed), where \( w_i \) are the weights, and \( v_i \) are the variables to be summed. \( b \) is a constant offset.

from 🇮 R2 tensors to be summed

Type: list of string
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

offset 🇧 The constant coefficient added to the final summation

Type: Scalar 🔗
Required: No

offset_as_parameter By default, the offset is declared as a buffer. Set this option to true to declare it as a (trainable) parameter.

Type: bool
Required: No
Default: false

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The sum

Type: string
Required: No
Default: to

weight_as_parameter By default, the weights are declared as buffers. Set this option to true to declare them as (trainable) parameters. This option takes a list of booleans, one for each weight. When the length of this list is 1, the boolean applies to all weights.

Type: list of bool
Required: No

weights 🇧 Weights associated with each variable. This option takes a list of weights, one for each coefficient. When the length of this list is 1, the same weight applies to all

Type: list of Scalar> 🔗
Required: No
Default: 1

Detailed documentation link

R2Multiplication

Multiplication of form \( A B \), where \( A \) and \( B \) are second order tensors. A and B can be inverted and/or transposed per request.

A 🇮 Variable A

Type: string
Required: No
Default: A

B 🇮 Variable B

Type: string
Required: No
Default: B

invert_A Whether to invert A

Type: bool
Required: No
Default: false

invert_B Whether to invert B

Type: bool
Required: No
Default: false

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The result of the multiplication

Type: string
Required: No
Default: to

transpose_A Whether to transpose A

Type: bool
Required: No
Default: false

transpose_B Whether to transpose B

Type: bool
Required: No
Default: false

Detailed documentation link

R2ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: R2 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

R2ToSR2

Extract the symmetric part of a R2 tensor

input 🇮 Second order tensor to split

Type: string
Required: No
Default: input

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

output 🇴 Output symmetric second order tensor

Type: string
Required: No
Default: output

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

R2ToWR2

Extract the skew symmetric part of a second order tensor

input 🇮 Second order tensor to split

Type: string
Required: No
Default: input

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

output 🇴 Output skew symmetric second order tensor

Type: string
Required: No
Default: output

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

R2VariableRate

Calculate the first order discrete time derivative of a variable as \( \dot{f} = \frac{f-f_n}{t-t_n} \), where \( f \) is the variable, \( f_n \) is the variable at the previous time step, and \( t \) is time.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇮 The variable being differentiated

Type: string
Required: No
Default: variable

Detailed documentation link

R3ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: R3 🔗
Required: Yes

Detailed documentation link

R3DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R3DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R3InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

R3IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R3IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R3IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R3ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: R3 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

R4ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: R4 🔗
Required: Yes

Detailed documentation link

R4DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R4DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R4InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

R4IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R4IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R4IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

R4ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: R4 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

RationalDegradationFunction

Power degradation function to degrade the elastic strain energy density, \( g = \frac{\left( 1-d \right)^p}{\left( 1-d \right)^p + Q\left(d \right)} \) where, \( Q\left(d \right) = b_{1}d\left( 1+b_{2}d+b_{2}b_{3}d^2 \right)\)

b1 🇵 Degradation parameter b_1

Type: Scalar 🔗
Required: Yes

b2 🇵 Degradation parameter b_2

Type: Scalar 🔗
Required: Yes

b3 🇵 Degradation parameter b_3

Type: Scalar 🔗
Required: Yes

degradation 🇴 Value of the degradation function

Type: string
Required: No
Default: degradation

eta Residual degradation when d = 1

Type: number
Required: No

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

phase 🇮 Phase-field variable

Type: string
Required: No
Default: phase

power 🇵 Power of the degradation function

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

ResolvedShear

Calculates the resolved shears as \( \tau_i = \sigma : Q \operatorname{sym}\left(d_i \otimes n_i \right) Q^T \) where \( \tau_i \) is the resolved shear on slip system i, \( \sigma \) is the Cauchy stress \( Q \) is the orientation matrix, \( d_i \) is the slip direction, and \( n_i \) is the slip system normal.

crystal_geometry The name of the data object with the crystallographic information

Type: string
Required: No
Default: crystal_geometry

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

orientation_matrix 🇮 The name of the orientation matrix

Type: string
Required: No
Default: orientation_matrix

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

resolved_shears 🇴 The name of the resolved shears

Type: string
Required: No
Default: resolved_shears

stress 🇮 The name of the Cauchy stress tensor

Type: string
Required: No
Default: stress

Detailed documentation link

RotConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: Rot 🔗
Required: Yes

Detailed documentation link

RotDynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

RotDynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

RotInputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

RotIntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

RotIntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

RotIntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

RotParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: Rot 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

RotationMatrix

Convert a Rot (rotation represented in Rodrigues format) to R2 (a full rotation matrix).

from 🇮 Rot to convert

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 R2 to store the resulting rotation matrix

Type: string
Required: No
Default: to

Detailed documentation link

SFFR4ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: SFFR4 🔗
Required: Yes

Detailed documentation link

SFFR4DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SFFR4DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SFFR4InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

SFFR4IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SFFR4IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SFFR4IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SFFR4ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: SFFR4 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

SFR3ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: SFR3 🔗
Required: Yes

Detailed documentation link

SFR3DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SFR3DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SFR3InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

SFR3IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SFR3IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SFR3IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SFR3ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: SFR3 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

SR2BackwardEulerTimeIntegration

Define the backward Euler time integration residual \( r = s - s_n - (t - t_n) \dot{s} \), where \(s\) is the variable being integrated, \(\dot{s}\) is the variable rate, and \(t\) is time. Subscripts \(n\) denote quantities from the previous time step.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate 🇮 Name of the variable rate.

Type: string
Required: No

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇮 Variable being integrated

Type: string
Required: No
Default: variable

Detailed documentation link

SR2BilinearInterpolation

Interpolate a SR2 as a function of the given argument. See neml2::Interpolation for rules on shapes of the interpolant and the argument. This object performs a bilinear interpolation.

abscissa1 🇧 Scalar defining the abscissa values of the first interpolation axis

Type: Scalar 🔗
Required: Yes

abscissa2 🇧 Scalar defining the abscissa values of the second interpolation axis

Type: Scalar 🔗
Required: Yes

argument1 🇮 First argument used to query the interpolant along the first axis

Type: string
Required: No
Default: argument1

argument2 🇮 Second argument used to query the interpolant along the second axis

Type: string
Required: No
Default: argument2

dim Intermediate dimension along which to interpolate

Type: number
Required: No

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

ordinate 🇵 SR2 defining the ordinate values of the interpolant

Type: SR2 🔗
Required: Yes

output 🇴 SR2 output of the interpolant. If not specified, the object name will be used as the output name.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

SR2ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: SR2 🔗
Required: Yes

Detailed documentation link

SR2Determinant

Calculate the Jacobian of a second order tensor.

determinant 🇴 The determinant of the input tensor

Type: string
Required: No
Default: determinant

input 🇮 The second order tensor to calculate the determinant of

Type: string
Required: No
Default: input

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

SR2DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SR2DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SR2ForwardEulerTimeIntegration

Perform forward Euler time integration defined as \( s = s_n + (t - t_n) \dot{s} \), where \(s\) is the variable being integrated, \(\dot{s}\) is the variable rate, and \(t\) is time. Subscripts \(n\) denote quantities from the previous time step.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate 🇮 Name of the variable rate.

Type: string
Required: No

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇴 Variable being integrated

Type: string
Required: No
Default: variable

Detailed documentation link

SR2InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

SR2IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SR2IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SR2IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SR2Invariant

Calculate the invariant of a symmetric second order tensor (of type SR2).

invariant 🇴 Invariant

Type: string
Required: No
Default: invariant

invariant_type Type of invariant. Options are: INVALID, EFFECTIVE_STRAIN, VONMISES, I2, I1

Type: EnumSelection
Required: No
Default: INVALID

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

tensor 🇮 Symmetric second order tensor to take the invariant of

Type: string
Required: No
Default: tensor

Detailed documentation link

SR2LinearCombination

Calculate linear combination of multiple SR2 tensors as \( u = w_i v_i + b \) (Einstein summation assumed), where \( w_i \) are the weights, and \( v_i \) are the variables to be summed. \( b \) is a constant offset.

from 🇮 SR2 tensors to be summed

Type: list of string
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

offset 🇧 The constant coefficient added to the final summation

Type: Scalar 🔗
Required: No

offset_as_parameter By default, the offset is declared as a buffer. Set this option to true to declare it as a (trainable) parameter.

Type: bool
Required: No
Default: false

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The sum

Type: string
Required: No
Default: to

weight_as_parameter By default, the weights are declared as buffers. Set this option to true to declare them as (trainable) parameters. This option takes a list of booleans, one for each weight. When the length of this list is 1, the boolean applies to all weights.

Type: list of bool
Required: No

weights 🇧 Weights associated with each variable. This option takes a list of weights, one for each coefficient. When the length of this list is 1, the same weight applies to all

Type: list of Scalar> 🔗
Required: No
Default: 1

Detailed documentation link

SR2LinearInterpolation

Interpolate a SR2 as a function of the given argument. See neml2::Interpolation for rules on shapes of the interpolant and the argument. This object performs a linear interpolation.

abscissa 🇧 Scalar defining the abscissa values of the interpolant

Type: Scalar 🔗
Required: Yes

argument 🇮 Argument used to query the interpolant

Type: string
Required: No
Default: argument

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

ordinate 🇵 SR2 defining the ordinate values of the interpolant

Type: SR2 🔗
Required: Yes

output 🇴 SR2 output of the interpolant. If not specified, the object name will be used as the output name.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

SR2ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: SR2 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

SR2ToR2

Convert a symmetric rank two tensor to a full tensor

input 🇮 Symmetric second order tensor to convert

Type: string
Required: No
Default: input

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

output 🇴 Output full second order tensor

Type: string
Required: No
Default: output

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

SR2TwoStageThermalAnnealing

Thermal annealing recovery for a hardening variable of type SR2. For temperatures below \( T_1 \) the model keeps the base model hardenign rate. For temperatures above \(T_1\) but below \(T_2 \) the model zeros the hardening rate. For temperatures above \(T_2\) the model replaces the hardening rate with \( \dot{h} = \frac{-h}{\tau} \) where \( \tau \) is the rate of recovery.

T1 🇵 First stage annealing temperature

Type: Scalar 🔗
Required: Yes

T2 🇵 Second stage annealing temperature

Type: Scalar 🔗
Required: Yes

base 🇮 Underlying base hardening variable

Type: string
Required: No
Default: base

base_rate 🇮 Base hardening rate

Type: string
Required: No
Default: base_rate

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

modified_rate 🇴 Output for the modified hardening rate.

Type: string
Required: No
Default: modified_rate

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

tau 🇵 Recovery rate for second stage annealing.

Type: Scalar 🔗
Required: Yes

temperature 🇮 Temperature

Type: string
Required: No
Default: temperature

Detailed documentation link

SR2VariableRate

Calculate the first order discrete time derivative of a variable as \( \dot{f} = \frac{f-f_n}{t-t_n} \), where \( f \) is the variable, \( f_n \) is the variable at the previous time step, and \( t \) is time.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇮 The variable being differentiated

Type: string
Required: No
Default: variable

Detailed documentation link

SSR4ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: SSR4 🔗
Required: Yes

Detailed documentation link

SSR4DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SSR4DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SSR4InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

SSR4IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SSR4IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SSR4IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SSR4ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: SSR4 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

SWR4ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: SWR4 🔗
Required: Yes

Detailed documentation link

SWR4DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SWR4DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SWR4InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

SWR4IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SWR4IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SWR4IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

SWR4ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: SWR4 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

ScalarBackwardEulerTimeIntegration

Define the backward Euler time integration residual \( r = s - s_n - (t - t_n) \dot{s} \), where \(s\) is the variable being integrated, \(\dot{s}\) is the variable rate, and \(t\) is time. Subscripts \(n\) denote quantities from the previous time step.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate 🇮 Name of the variable rate.

Type: string
Required: No

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇮 Variable being integrated

Type: string
Required: No
Default: variable

Detailed documentation link

ScalarBilinearInterpolation

Interpolate a Scalar as a function of the given argument. See neml2::Interpolation for rules on shapes of the interpolant and the argument. This object performs a bilinear interpolation.

abscissa1 🇧 Scalar defining the abscissa values of the first interpolation axis

Type: Scalar 🔗
Required: Yes

abscissa2 🇧 Scalar defining the abscissa values of the second interpolation axis

Type: Scalar 🔗
Required: Yes

argument1 🇮 First argument used to query the interpolant along the first axis

Type: string
Required: No
Default: argument1

argument2 🇮 Second argument used to query the interpolant along the second axis

Type: string
Required: No
Default: argument2

dim Intermediate dimension along which to interpolate

Type: number
Required: No

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

ordinate 🇵 Scalar defining the ordinate values of the interpolant

Type: Scalar 🔗
Required: Yes

output 🇴 Scalar output of the interpolant. If not specified, the object name will be used as the output name.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

ScalarConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: Scalar 🔗
Required: Yes

Detailed documentation link

ScalarDynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

ScalarDynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

ScalarForwardEulerTimeIntegration

Perform forward Euler time integration defined as \( s = s_n + (t - t_n) \dot{s} \), where \(s\) is the variable being integrated, \(\dot{s}\) is the variable rate, and \(t\) is time. Subscripts \(n\) denote quantities from the previous time step.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate 🇮 Name of the variable rate.

Type: string
Required: No

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇴 Variable being integrated

Type: string
Required: No
Default: variable

Detailed documentation link

ScalarInputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

ScalarIntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

ScalarIntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

ScalarIntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

ScalarLinearCombination

Calculate linear combination of multiple Scalar tensors as \( u = w_i v_i + b \) (Einstein summation assumed), where \( w_i \) are the weights, and \( v_i \) are the variables to be summed. \( b \) is a constant offset.

from 🇮 Scalar tensors to be summed

Type: list of string
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

offset 🇧 The constant coefficient added to the final summation

Type: Scalar 🔗
Required: No

offset_as_parameter By default, the offset is declared as a buffer. Set this option to true to declare it as a (trainable) parameter.

Type: bool
Required: No
Default: false

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The sum

Type: string
Required: No
Default: to

weight_as_parameter By default, the weights are declared as buffers. Set this option to true to declare them as (trainable) parameters. This option takes a list of booleans, one for each weight. When the length of this list is 1, the boolean applies to all weights.

Type: list of bool
Required: No

weights 🇧 Weights associated with each variable. This option takes a list of weights, one for each coefficient. When the length of this list is 1, the same weight applies to all

Type: list of Scalar> 🔗
Required: No
Default: 1

Detailed documentation link

ScalarLinearInterpolation

Interpolate a Scalar as a function of the given argument. See neml2::Interpolation for rules on shapes of the interpolant and the argument. This object performs a linear interpolation.

abscissa 🇧 Scalar defining the abscissa values of the interpolant

Type: Scalar 🔗
Required: Yes

argument 🇮 Argument used to query the interpolant

Type: string
Required: No
Default: argument

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

ordinate 🇵 Scalar defining the ordinate values of the interpolant

Type: Scalar 🔗
Required: Yes

output 🇴 Scalar output of the interpolant. If not specified, the object name will be used as the output name.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

ScalarMultiplication

Calculate the product of multiple Scalar variables with a constant scaling coefficient. Using reciprocal, one can have the reciprocity of each variable

from 🇮 Scalar variables to be multiplied

Type: list of string
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reciprocal List of boolens, one for each variable, in which the reciprocity of the corresponding variable is taken. When the length of this list is 1, the same reciprocal condition applies to all variables.

Type: list of bool
Required: No

scaling 🇵 The scaling coefficient to multiply to the final product

Type: Scalar 🔗
Required: No
Default: 1

to 🇴 The multiplicative product

Type: string
Required: No
Default: to

Detailed documentation link

ScalarParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

ScalarToDiagonalSR2

Create a diagonal symmetric rank 2 tensor with values filled by a scalar

input 🇮 Scalar to convert

Type: string
Required: No
Default: input

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

output 🇴 Output diagonal symmetric second order tensor

Type: string
Required: No
Default: output

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

ScalarTwoStageThermalAnnealing

Thermal annealing recovery for a hardening variable of type Scalar. For temperatures below \( T_1 \) the model keeps the base model hardenign rate. For temperatures above \(T_1\) but below \(T_2 \) the model zeros the hardening rate. For temperatures above \(T_2\) the model replaces the hardening rate with \( \dot{h} = \frac{-h}{\tau} \) where \( \tau \) is the rate of recovery.

T1 🇵 First stage annealing temperature

Type: Scalar 🔗
Required: Yes

T2 🇵 Second stage annealing temperature

Type: Scalar 🔗
Required: Yes

base 🇮 Underlying base hardening variable

Type: string
Required: No
Default: base

base_rate 🇮 Base hardening rate

Type: string
Required: No
Default: base_rate

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

modified_rate 🇴 Output for the modified hardening rate.

Type: string
Required: No
Default: modified_rate

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

tau 🇵 Recovery rate for second stage annealing.

Type: Scalar 🔗
Required: Yes

temperature 🇮 Temperature

Type: string
Required: No
Default: temperature

Detailed documentation link

ScalarVariableRate

Calculate the first order discrete time derivative of a variable as \( \dot{f} = \frac{f-f_n}{t-t_n} \), where \( f \) is the variable, \( f_n \) is the variable at the previous time step, and \( t \) is time.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇮 The variable being differentiated

Type: string
Required: No
Default: variable

Detailed documentation link

SingleSlipStrengthMap

Calculates the slip system strength for all slip systems as \( \hat{\tau}_i = \bar{\tau} + \tau_0 \) where \( \hat{\tau}_i \) is the strength for slip system i, \( \bar{\tau} \) is an evolving slip system strength (one value of all systems), defined by another object, and \( \tau_0 \) is a constant strength.

constant_strength 🇵 The constant slip system strength

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

slip_hardening 🇮 The name of the evolving, scalar strength

Type: string
Required: No
Default: slip_hardening

slip_strengths 🇴 Name of the slip system strengths

Type: string
Required: No
Default: slip_strengths

Detailed documentation link

SlopeSaturationVoceIsotropicHardening

SlopeSaturationVoce isotropic hardening model, \( \dot{h} = \theta_0 \left(1 - \frac{h}{R} \right) \varepsilon_p \), where \( R \) is the isotropic hardening upon saturation, and \( \theta_0 \) is the initial hardening rate. In addition to the reparameterization, this model differences from the VoceIsotropicHardening model in that it defines the hardening rate in a non-assocative manner. This is sometimes handy, for example in supplementing the model with static recovery.

flow_rate 🇮 Flow rate

Type: string
Required: No
Default: flow_rate

initial_hardening_rate 🇵 Initial hardening rate

Type: Scalar 🔗
Required: Yes

isotropic_hardening 🇮 Isotropic hardening variable

Type: string
Required: No
Default: isotropic_hardening

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

saturated_hardening 🇵 Saturated isotropic hardening

Type: Scalar 🔗
Required: Yes

Detailed documentation link

SumSlipRates

Calculates the sum of the absolute value of all the slip rates as \( \sum_{i=1}^{n_{slip}} \left| \dot{\gamma}_i \right| \).

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

slip_rates 🇮 The name of individual slip rates

Type: string
Required: No
Default: slip_rates

sum_slip_rates 🇴 The output name for the scalar sum of the slip rates

Type: string
Required: No
Default: sum_slip_rates

Detailed documentation link

SwellingAndPhaseChangeDeformationJacobian

Define the linear isotropic phase change deformation Jacobian for a freezing liquid or a melting solid, i.e. \( J = \left( 1 + \alpha c \phi^f + (1-c) \phi^f \Delta \Omega \right) \), where \( \alpha \) is the coefficient of swelling, \( \Delta \Omega \) is relative difference of the reference volume between the two phases, \( \phi^f \) is the fluid fraction associated with swelling, and \( c \) is the phase fraction.

fluid_fraction 🇮 Volume fraction of the fluid phase.

Type: string
Required: No
Default: fluid_fraction

jacobian 🇴 Phase change deformation Jacobian

Type: string
Required: No
Default: jacobian

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

phase_fraction 🇵 Phase fraction during the phase change. 0 means all solid, 1 means all liquid.

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reference_volume_difference 🇵 Relative difference between the reference volumes of the two phases.

Type: Scalar 🔗
Required: Yes

swelling_coefficient 🇵 Coefficient of phase expansion

Type: Scalar 🔗
Required: Yes

Detailed documentation link

SymmetricHermiteInterpolation

Define the symmetric Hermite interpolation function, taking the form of \( \dfrac{1}{x_h-x_l}(24c^2-32c^3) \) for \( 0 le c le 0.5 \); \( \dfrac{1}{x_h-x_l} (24(1-c)^2 - 32(1-c)^3) \) for \( 0.5 le c le 1 \), and 0.0 otherwise. Here, \( c = \frac{x-x_l}{x_h-x_l} \) where \(x_l\) and \(x_h\) are the lower and upper bound for rescaling the input argument.

argument 🇮 Argument of the smooth step function

Type: string
Required: No
Default: argument

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

lower_bound 🇧 Lower bound of the argument

Type: Scalar 🔗
Required: Yes

output 🇴 Value of the smooth step function. If not specified, the object name will be used as the output name.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

upper_bound 🇧 Upper bound of the argument

Type: Scalar 🔗
Required: Yes

Detailed documentation link

ThermalDeformationJacobian

Define the linear isotropic thermal deformation Jacobian, i.e. \( J = 1 + \alpha (T - T_0) \), where \( \alpha \) is the coefficient of thermal expansion (CTE), \( T \) is the temperature, and \( T_0 \) is the reference (stress-free) temperature.

CTE 🇵 Coefficient of thermal expansion

Type: Scalar 🔗
Required: Yes

jacobian 🇴 Thermal deformation Jacobian

Type: string
Required: No
Default: jacobian

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reference_temperature 🇧 Reference (stress-free) temperature

Type: Scalar 🔗
Required: Yes

temperature 🇮 Temperature

Type: string
Required: No
Default: temperature

Detailed documentation link

ThermalEigenstrain

Define the (cummulative, as opposed to instantaneous) linear isotropic thermal eigenstrain, i.e. \( \boldsymbol{\varepsilon}_T = \alpha (T - T_0) \boldsymbol{I} \), where \( \alpha \) is the coefficient of thermal expansion (CTE), \( T \) is the temperature, and \( T_0 \) is the reference (stress-free) temperature.

CTE 🇵 Coefficient of thermal expansion

Type: Scalar 🔗
Required: Yes

eigenstrain 🇴 Eigenstrain

Type: string
Required: No
Default: eigenstrain

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reference_temperature 🇧 Reference (stress-free) temperature

Type: Scalar 🔗
Required: Yes

temperature 🇮 Temperature

Type: string
Required: No
Default: temperature

Detailed documentation link

VanGenuchtenCapillaryPressure

Relate the porous flow capillary pressure to the effective saturation using the van Genuchten correlation for capillary pressure, taking the form of \( a \left( S_e^{-\frac{1}{m}} - 1 \right)^{1-m} \). Here \( S_e \) is the effective saturation, \( a \) and \( m \) are shape parameters

a 🇵 Shape parameter a

Type: Scalar 🔗
Required: Yes

capillary_pressure 🇴 Capillary pressure.

Type: string
Required: No
Default: capillary_pressure

effective_saturation 🇮 The effective saturation

Type: string
Required: No
Default: effective_saturation

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

log_extension Whether to apply logarithmic extension

Type: bool
Required: No
Default: false

m 🇵 Shape parameter m

Type: Scalar 🔗
Required: Yes

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

transition_saturation The transition value of the effective saturation below which to apply the logarithmic extension

Type: number
Required: No

Detailed documentation link

VecBackwardEulerTimeIntegration

Define the backward Euler time integration residual \( r = s - s_n - (t - t_n) \dot{s} \), where \(s\) is the variable being integrated, \(\dot{s}\) is the variable rate, and \(t\) is time. Subscripts \(n\) denote quantities from the previous time step.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate 🇮 Name of the variable rate.

Type: string
Required: No

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇮 Variable being integrated

Type: string
Required: No
Default: variable

Detailed documentation link

VecBilinearInterpolation

Interpolate a Vec as a function of the given argument. See neml2::Interpolation for rules on shapes of the interpolant and the argument. This object performs a bilinear interpolation.

abscissa1 🇧 Scalar defining the abscissa values of the first interpolation axis

Type: Scalar 🔗
Required: Yes

abscissa2 🇧 Scalar defining the abscissa values of the second interpolation axis

Type: Scalar 🔗
Required: Yes

argument1 🇮 First argument used to query the interpolant along the first axis

Type: string
Required: No
Default: argument1

argument2 🇮 Second argument used to query the interpolant along the second axis

Type: string
Required: No
Default: argument2

dim Intermediate dimension along which to interpolate

Type: number
Required: No

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

ordinate 🇵 Vec defining the ordinate values of the interpolant

Type: Vec 🔗
Required: Yes

output 🇴 Vec output of the interpolant. If not specified, the object name will be used as the output name.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

VecConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: Vec 🔗
Required: Yes

Detailed documentation link

VecDynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

VecDynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

VecForwardEulerTimeIntegration

Perform forward Euler time integration defined as \( s = s_n + (t - t_n) \dot{s} \), where \(s\) is the variable being integrated, \(\dot{s}\) is the variable rate, and \(t\) is time. Subscripts \(n\) denote quantities from the previous time step.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate 🇮 Name of the variable rate.

Type: string
Required: No

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇴 Variable being integrated

Type: string
Required: No
Default: variable

Detailed documentation link

VecInputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

VecIntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

VecIntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

VecIntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

VecLinearCombination

Calculate linear combination of multiple Vec tensors as \( u = w_i v_i + b \) (Einstein summation assumed), where \( w_i \) are the weights, and \( v_i \) are the variables to be summed. \( b \) is a constant offset.

from 🇮 Vec tensors to be summed

Type: list of string
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

offset 🇧 The constant coefficient added to the final summation

Type: Scalar 🔗
Required: No

offset_as_parameter By default, the offset is declared as a buffer. Set this option to true to declare it as a (trainable) parameter.

Type: bool
Required: No
Default: false

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The sum

Type: string
Required: No
Default: to

weight_as_parameter By default, the weights are declared as buffers. Set this option to true to declare them as (trainable) parameters. This option takes a list of booleans, one for each weight. When the length of this list is 1, the boolean applies to all weights.

Type: list of bool
Required: No

weights 🇧 Weights associated with each variable. This option takes a list of weights, one for each coefficient. When the length of this list is 1, the same weight applies to all

Type: list of Scalar> 🔗
Required: No
Default: 1

Detailed documentation link

VecLinearInterpolation

Interpolate a Vec as a function of the given argument. See neml2::Interpolation for rules on shapes of the interpolant and the argument. This object performs a linear interpolation.

abscissa 🇧 Scalar defining the abscissa values of the interpolant

Type: Scalar 🔗
Required: Yes

argument 🇮 Argument used to query the interpolant

Type: string
Required: No
Default: argument

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

ordinate 🇵 Vec defining the ordinate values of the interpolant

Type: Vec 🔗
Required: Yes

output 🇴 Vec output of the interpolant. If not specified, the object name will be used as the output name.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

VecParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: Vec 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

VecVariableRate

Calculate the first order discrete time derivative of a variable as \( \dot{f} = \frac{f-f_n}{t-t_n} \), where \( f \) is the variable, \( f_n \) is the variable at the previous time step, and \( t \) is time.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇮 The variable being differentiated

Type: string
Required: No
Default: variable

Detailed documentation link

VoceIsotropicHardening

Voce isotropic hardening model, \( h = R \left[ 1 - \exp(-d \bar{\varepsilon}_p) \right] \), where \( R \) is the isotropic hardening upon saturation, and \( d \) is the hardening rate.

equivalent_plastic_strain 🇮 Equivalent plastic strain

Type: string
Required: No
Default: equivalent_plastic_strain

isotropic_hardening 🇴 Isotropic hardening

Type: string
Required: No
Default: isotropic_hardening

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

saturated_hardening 🇵 Saturated isotropic hardening

Type: Scalar 🔗
Required: Yes

saturation_rate 🇵 Hardening saturation rate

Type: Scalar 🔗
Required: Yes

Detailed documentation link

VoceSingleSlipHardeningRule

Voce hardening for a SingleSlipStrength type model defined by \( \dot{\tau} = \theta_0 \left( 1 - \frac{\tau}{\tau_f} \right) \sum_{i=1}^{n_{slip}} \left| \dot{\gamma}_i \right| \) where \( \theta_0 \) is the initial rate of work hardening, \( \tau_f \) is the saturated, maximum value of the slip system strength, and \( \dot{\gamma}_i \) is the slip rate on each system.

initial_slope 🇵 The initial rate of hardening

Type: Scalar 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

saturated_hardening 🇵 The final, saturated value of the slip system strength

Type: Scalar 🔗
Required: Yes

slip_hardening 🇮 Name of current values of slip hardening

Type: string
Required: No
Default: slip_hardening

sum_slip_rates 🇮 Name of tensor containing the sum of the slip rates

Type: string
Required: No
Default: sum_slip_rates

Detailed documentation link

VolumeAdjustDeformationGradient

Calculate the volume-adjusted deformation gradient, i.e. \( F_e = J^{-\frac{1}/{3}} F \), where \( F \) is the pre-adjusted deformation gradient and \( J \) is the total jacobian of the volumetric deformation gradients to be removed.

input 🇮 Input deformation gradient

Type: string
Required: No
Default: input

jacobian 🇮 The Jacobian that controls the volume adjustment of the input deformation gradient

Type: string
Required: No
Default: jacobian

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

output 🇴 Output adjusted deformation gradient

Type: string
Required: No
Default: output

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

Detailed documentation link

VolumeChangeEigenstrain

Define the (cumulative, as opposed to instantaneous) linear isotropic volume expansion eigenstrain, i.e. \( \boldsymbol{\varepsilon}_V = (\frac{V}{V0})^(1/3)-1 \boldsymbol{I} \), where \( V \) is the current volume, and \( V0 \) is the reference (initial) volume.

eigenstrain 🇴 Eigenstrain

Type: string
Required: No
Default: eigenstrain

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

reference_volume 🇵 Reference (initial) volume

Type: Scalar 🔗
Required: Yes

volume 🇮 Volume

Type: string
Required: No
Default: volume

Detailed documentation link

WFFR4ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: WFFR4 🔗
Required: Yes

Detailed documentation link

WFFR4DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WFFR4DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WFFR4InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

WFFR4IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WFFR4IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WFFR4IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WFFR4ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: WFFR4 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

WR2ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: WR2 🔗
Required: Yes

Detailed documentation link

WR2DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WR2DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WR2ExplicitExponentialTimeIntegration

Perform explicit discrete exponential time integration of a rotation. The update can be written as \( s = \exp\left[ (t-t_n)\dot{s}\right] \circ s_n \), where \( \circ \) denotes the rotation operator.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate 🇮 Name of the variable rate.

Type: string
Required: No

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇴 Variable being integrated

Type: string
Required: No
Default: variable

Detailed documentation link

WR2ImplicitExponentialTimeIntegration

Define the implicit discrete exponential time integration residual of a rotation variable. The residual can be written as \( r = s - \exp\left[ (t-t_n)\dot{s}\right] \circ s_n \), where \( \circ \) denotes the rotation operator.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

rate 🇮 Name of the variable rate.

Type: string
Required: No

time 🇮 Time

Type: string
Required: No
Default: t

variable 🇮 Variable being integrated

Type: string
Required: No
Default: variable

Detailed documentation link

WR2InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

WR2IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WR2IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WR2IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WR2ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: WR2 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

WSR4ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: WSR4 🔗
Required: Yes

Detailed documentation link

WSR4DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WSR4DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WSR4InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

WSR4IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WSR4IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WSR4IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WSR4ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: WSR4 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

WWR4ConstantParameter

A parameter that is just a constant value, generally used to refer to a parameter in more than one downstream object.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 The output parameter. If not specified, the object name will be used.

Type: string
Required: No

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

value 🇵 The constant value of the parameter

Type: WWR4 🔗
Required: Yes

Detailed documentation link

WWR4DynamicMean

Average a dynamic dimension

dim The dimension to average over

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WWR4DynamicSum

Sum a dynamic dimension

dim The dimension to sum

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WWR4InputParameter

A parameter whose value is provided by an input variable. This object is not intended to be used directly in the input file.

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

parameter 🇴 Output parameter

Type: string
Required: No
Default: parameter

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

variable 🇮 The input variable that defines this parameter

Type: string
Required: No
Default: variable

Detailed documentation link

WWR4IntermediateDiff

Finite difference along an intermediate dimension

dim Intermediate dimension to take the finite difference

Type: number
Required: Yes

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

n Order of the differentiation

Type: number
Required: No
Default: 1

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WWR4IntermediateMean

Average an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WWR4IntermediateSum

Sum an intermediate dimension

from 🇮 Variable to reduce

Type: string
Required: No
Default: from

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The reduced variable

Type: string
Required: No
Default: to

Detailed documentation link

WWR4ParameterToVariable

Convert the parameter to variable.

from 🇵 The input parameter

Type: WWR4 🔗
Required: Yes

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

to 🇴 The name of the variable

Type: string
Required: No
Default: to

Detailed documentation link

YieldFunction

Classical macroscale plasticity yield function, \( f = \bar{\sigma} - \sigma_y - h \), where \( \bar{\sigma} \) is the effective stress, \( \sigma_y \) is the yield stress, and \( h \) is the isotropic hardening.

effective_stress 🇮 Effective stress

Type: string
Required: No
Default: effective_stress

isotropic_hardening 🇮 Isotropic hardening

Type: string
Required: No

jit Use JIT compilation for the forward operator

Type: bool
Required: No
Default: true

production Production mode. This option is used to disable features like function graph tracking and tensor version tracking which are useful for training (i.e., calibrating model parameters) but are not necessary in production runs.

Type: bool
Required: No
Default: false

yield_function 🇴 Yield function

Type: string
Required: No
Default: yield_function

yield_stress 🇵 Yield stress

Type: Scalar 🔗
Required: Yes

Detailed documentation link

Table of Contents

Available objects and their input file syntax

AdvectiveStress

ArrheniusParameter

AssociativeIsotropicPlasticHardening

AssociativeJ2FlowDirection

AssociativeKinematicPlasticHardening

AssociativePlasticFlow

AvramiErofeevNucleation

BrooksCoreyCapillaryPressure

ChabochePlasticHardening

ComposedModel

ConstantExtrapolationPredictor

ContractingGeometry

CopyMillerIndex

CopyQuaternion

CopyR2

CopyR3

CopyR4

CopyRot

CopySFFR4

CopySFR3

CopySR2

CopySSR4

CopySWR4

CopyScalar

CopyVec

CopyWFFR4

CopyWR2

CopyWSR4

CopyWWR4

CrackGeometricFunctionAT1

CrackGeometricFunctionAT2

CrystalPlasticityStrainPredictor

CubicElasticityTensor

CylindricalChannelGeometry

DiffusionLimitedReaction

DislocationObstacleStrengthMap

EffectiveSaturation

EffectiveVolume

ElasticStrainRate

ExponentialLawPermeability

FBComplementarity

FiniteVolumeAppendBoundaryCondition

FiniteVolumeGradient

FiniteVolumeUpwindedAdvectiveFlux

FixOrientation

FredrickArmstrongPlasticHardening

GTNYieldFunction

GeneralElasticity

GreenLagrangeStrain

GursonCavitation

HermiteSmoothStep

ImplicitUpdate

IsotropicElasticityTensor

IsotropicMandelStress

KocksMeckingActivationEnergy

KocksMeckingFlowSwitch

KocksMeckingFlowViscosity

KocksMeckingIntercept

KocksMeckingRateSensitivity

KocksMeckingYieldStress

KozenyCarmanPermeability

LinearExtrapolationPredictor

LinearIsotropicElasticJ2TrialStressUpdate

LinearIsotropicElasticity

LinearIsotropicHardening

LinearIsotropicStrainEnergyDensity

LinearKinematicHardening

LinearSingleSlipHardeningRule

LinearlyInterpolateToCellEdges

MillerIndexConstantParameter

MillerIndexDynamicMean

MillerIndexDynamicSum

MillerIndexInputParameter

MillerIndexIntermediateDiff

MillerIndexIntermediateMean

MillerIndexIntermediateSum

MillerIndexParameterToVariable

MixedControlSetup