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Merge pull request #78 from dewenyushu/elastic_inversion
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Add elastic inversion capability using batch materials
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lynnmunday authored Jun 29, 2023
2 parents 0dcf360 + 259241b commit 28f6d82
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22 changes: 22 additions & 0 deletions doc/content/source/userobjects/BatchStressGrad.md
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# BatchStressGrad

## Description

This `UserObject` computes double contraction of the elasticity tensor derivative and the forward mechanical strain, i.e.,
\begin{equation}
\underbrace{\frac{\partial \boldsymbol{C}}{\partial p}}_{\text{elasticity tensor derivative}} \underbrace{(\boldsymbol{L} u)}_{\text{forward strain}}
\end{equation}
as a batch material.
Here, $\boldsymbol{C}$ is the elasticity tensor, $p$ is the interested parameter, $\boldsymbol{L}$ is the symmetric strain operator for the elasticity problem, and $\boldsymbol{L} u$ is the strain from the forward problem. This object requires the elasticity tensor derivative material property (i.e., $\frac{\partial \boldsymbol{C}}{\partial p}$) as its input.

This object is used together with [AdjointStrainStressGradInnerProduct](/AdjointStrainStressGradInnerProduct.md) in a linear elastic inversion problem.

## Example Input File Syntax

!listing test/tests/bimaterial_elastic_inversion_batch_mat/grad.i block=UserObjects/stress_grad_lambda

!syntax parameters /UserObjects/BatchStressGrad

!syntax inputs /UserObjects/BatchStressGrad

!syntax children /UserObjects/BatchStressGrad
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# AdjointStrainStressGradInnerProduct

!syntax description /VectorPostprocessors/AdjointStrainStressGradInnerProduct

## Description

This `VectorPostprocessor` is utilized in a mechanical inverse optimization problem (see [Inverse Optimization Theory](/InvOptTheory.md)) for computing the gradient of objective function with respect to a parameter of interest.

Specifically, the objective function is defined as the sum of the regularization and the displacement mismatch (between the simulation and the measurement data at specific locations) as follows:
\begin{equation}
F({u}, \boldsymbol{p}) = ||\boldsymbol{S}{u} - \boldsymbol{u}_m ||^2 + R({u}, \boldsymbol{p}),
\end{equation}
where ${u}$ denotes the displacement from the forward problem, $\boldsymbol{S}$ is the sampling operator, $\boldsymbol{u}_m$ are the measurements, $\boldsymbol{p} = [p_1, p_2, ..., p_n]$ is the vector of parameters, and $R$ is the regularization term.

The gradient of objective function with respect to one scalar parameter ($p_i$) is
\begin{equation}
\frac{\text{d}{F}}{\text{d}p_i} = - \int \underbrace{(\boldsymbol{L}\lambda)^T}_{\text{adjoint strain}} \underbrace{\frac{\partial \boldsymbol{C}}{\partial p_i} (\boldsymbol{L} u)}_{\text{gradient of stress}} \text{d}\Omega,
\end{equation}
where ${F}$ is the objective function, $\boldsymbol{L}$ is the symmetric strain operator for the elasticity problem, $\lambda$ is the adjoint displacement, $\boldsymbol{C}$ is the elasticity tensor, and $p_i$ is the interested scalar parameter.

Specifically, this object takes the `adjoint strain` and the `gradient of stress w.r.t. parameter` as inputs, computes the double contraction of the two inputs, and integrate over the entire domain. Specifically, the `adjoint strain` is the strain from the adjoint problem, the `gradient of stress w.r.t. parameter` should be a batch material (e.g., [BatchStressGrad](/BatchStressGrad.md)).

## Example Input File Syntax

!listing test/tests/bimaterial_elastic_inversion_batch_mat/grad.i block=VectorPostprocessors/grad_lambda

!syntax parameters /VectorPostprocessors/AdjointStrainStressGradInnerProduct

!syntax inputs /VectorPostprocessors/AdjointStrainStressGradInnerProduct

!syntax children /VectorPostprocessors/AdjointStrainStressGradInnerProduct
33 changes: 33 additions & 0 deletions include/userobjects/BatchStressGrad.h
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//* This file is part of the MOOSE framework
//* https://www.mooseframework.org
//*
//* All rights reserved, see COPYRIGHT for full restrictions
//* https://github.com/idaholab/moose/blob/master/COPYRIGHT
//*
//* Licensed under LGPL 2.1, please see LICENSE for details
//* https://www.gnu.org/licenses/lgpl-2.1.html

#pragma once

#include "BatchMaterial.h"

typedef BatchMaterial<
// tuple representation
BatchMaterialUtils::TupleStd,
// output data type
RankTwoTensor,
// gathered input data types:
BatchMaterialUtils::GatherMatProp<RankFourTensor>,
BatchMaterialUtils::GatherMatProp<RankTwoTensor>>

BatchStressGradParent;

class BatchStressGrad : public BatchStressGradParent
{
public:
static InputParameters validParams();

BatchStressGrad(const InputParameters & params);

void batchCompute() override;
};
31 changes: 31 additions & 0 deletions include/vectorpostprocessors/AdjointStrainStressGradInnerProduct.h
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//* This file is part of the MOOSE framework
//* https://www.mooseframework.org
//*
//* All rights reserved, see COPYRIGHT for full restrictions
//* https://github.com/idaholab/moose/blob/master/COPYRIGHT
//*
//* Licensed under LGPL 2.1, please see LICENSE for details
//* https://www.gnu.org/licenses/lgpl-2.1.html

#pragma once

#include "ElementOptimizationFunctionInnerProduct.h"
#include "BatchStressGrad.h"

class AdjointStrainStressGradInnerProduct : public ElementOptimizationFunctionInnerProduct
{
public:
static InputParameters validParams();

AdjointStrainStressGradInnerProduct(const InputParameters & parameters);

protected:
virtual Real computeQpInnerProduct() override;
/// Base name of the material system
const std::string _base_name;
/// Holds adjoint strain at current quadrature points
const MaterialProperty<RankTwoTensor> & _adjoint_strain;
/// UO that holds gradient of stress wrt material parameter at current quadrature points
const BatchStressGrad & _stress_grad_uo;
const BatchStressGrad::OutputVector & _stress_grad_uo_output;
};
58 changes: 58 additions & 0 deletions src/userobjects/BatchStressGrad.C
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//* This file is part of the MOOSE framework
//* https://www.mooseframework.org
//*
//* All rights reserved, see COPYRIGHT for full restrictions
//* https://github.com/idaholab/moose/blob/master/COPYRIGHT
//*
//* Licensed under LGPL 2.1, please see LICENSE for details
//* https://www.gnu.org/licenses/lgpl-2.1.html

#include "BatchStressGrad.h"
#include "libmesh/int_range.h"

registerMooseObject("isopodApp", BatchStressGrad);

InputParameters
BatchStressGrad::validParams()
{
auto params = BatchStressGradParent::validParams();
params.addRequiredParam<MaterialPropertyName>(
"elasticity_tensor_derivative",
"Name of the elasticity tensor derivative material property.");
params.setDocString(
"execution_order_group",
"BatchStressGrad userObject needs to be completely executed before vectorPostprocessors.");
params.set<int>("execution_order_group") = -1;
params.addClassDescription("Compute the double contraction of the elasticity tensor derivative "
"and the forward mechanical strain");
return params;
}

BatchStressGrad::BatchStressGrad(const InputParameters & params)
: BatchStressGradParent(params,
// here we pass the derivative of elasticity tensor wrt to the parameter
"elasticity_tensor_derivative",
// here we pass in the forward strain
"forward_mechanical_strain")
{
}

/*
Note: The following calculation is currently specialized for a linear elastic inverse optimization
problem. This will be swapped out later on when we can get the gradient of stress w.r.t. the
interested parameter from NEML for general material models.
*/
void
BatchStressGrad::batchCompute()
{
for (const auto i : index_range(_input_data))
{
const auto & input = _input_data[i];
auto & output = _output_data[i];

const auto & elasticity_dev = std::get<0>(input);
const auto & strain = std::get<1>(input);

output = elasticity_dev * strain;
}
}
49 changes: 49 additions & 0 deletions src/vectorpostprocessors/AdjointStrainStressGradInnerProduct.C
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//* This file is part of the MOOSE framework
//* https://www.mooseframework.org
//*
//* All rights reserved, see COPYRIGHT for full restrictions
//* https://github.com/idaholab/moose/blob/master/COPYRIGHT
//*
//* Licensed under LGPL 2.1, please see LICENSE for details
//* https://www.gnu.org/licenses/lgpl-2.1.html

#include "AdjointStrainStressGradInnerProduct.h"

registerMooseObject("isopodApp", AdjointStrainStressGradInnerProduct);

InputParameters
AdjointStrainStressGradInnerProduct::validParams()
{
InputParameters params = ElementOptimizationFunctionInnerProduct::validParams();
params.addRequiredParam<UserObjectName>(
"stress_grad_name",
"Name of the stress gradient user object with respect to the material parameter");

params.addRequiredParam<MaterialPropertyName>(
"adjoint_strain_name", "Name of the strain property in the adjoint problem");

params.addClassDescription(
"Compute the parameter gradient for linear elastic material inversion");
return params;
}
AdjointStrainStressGradInnerProduct::AdjointStrainStressGradInnerProduct(
const InputParameters & parameters)
: ElementOptimizationFunctionInnerProduct(parameters),
_base_name(isParamValid("base_name") ? getParam<std::string>("base_name") + "_" : ""),
_adjoint_strain(getMaterialPropertyByName<RankTwoTensor>(
getParam<MaterialPropertyName>("adjoint_strain_name"))),
_stress_grad_uo(getUserObject<BatchStressGrad>("stress_grad_name")),
_stress_grad_uo_output(_stress_grad_uo.getOutputData())
{
}

Real
AdjointStrainStressGradInnerProduct::computeQpInnerProduct()
{
if (!_stress_grad_uo.outputReady())
mooseError("Stress gradient batch material property is not ready to output.");

const auto index = _stress_grad_uo.getIndex(_current_elem->id());

return -_adjoint_strain[_qp].doubleContraction(_stress_grad_uo_output[index + _qp]);
}
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grad_lambda,grad_mu,lambda,measurement_time,measurement_values,measurement_xcoord,measurement_ycoord,measurement_zcoord,misfit_values,mu,simulation_values
5.1698615078396e-11,5.2394323056988e-11,4.9999752463318,0,4.46462,-1,-1,0,9.2479240265675e-08,1.0000001055133,4.4646200924792
5.097187284528e-12,3.5417284419815e-11,4.0000666870441,0,6.447155,-1,0,0,5.2641227377137e-08,2.0000064790597,6.4471550526412
-2.7212788369455e-12,8.6258766757591e-12,2.9997143457064,0,8.434803,-1,1,0,-1.0044113984975e-07,2.9999940961679,8.4348028995589
0,0,0,0,4.176264,0,-1,0,-1.14358395642e-07,0,4.1762638856416
0,0,0,0,6.172984,0,0,0,-1.7726937251439e-07,0,6.1729838227306
0,0,0,0,8.200859,0,1,0,1.9391855410333e-07,0,8.2008591939186
0,0,0,0,4.049477,1,-1,0,2.2853767767117e-08,0,4.0494770228538
0,0,0,0,6.052499,1,0,0,1.1289934853664e-07,0,6.0524991128993
0,0,0,0,8.079385,1,1,0,-8.6613697547477e-08,0,8.0793849133863
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