RankTwoTensor
TensorMechanicsPlasticMeanCapTC::dhardPotential_dstress(const RankTwoTensor & stress, Real intnl) const
{
const Real tr = stress.trace();
const Real t_str = tensile_strength(intnl);
if (tr >= t_str)
return RankTwoTensor();
const Real c_str = compressive_strength(intnl);
if (tr <= c_str)
return RankTwoTensor();
return - std::sin(M_PI * (tr - c_str) / (t_str - c_str)) * M_PI / (t_str - c_str) * stress.dtrace();
}
void
RankTwoTensorTest::rotateTest()
{
Real sqrt2 = 0.707106781187;
RealTensorValue rtv0(sqrt2, -sqrt2, 0, sqrt2, sqrt2, 0, 0, 0, 1); // rotation about "0" axis
RealTensorValue rtv1(sqrt2, 0, -sqrt2, 0, 1, 0, sqrt2, 0, sqrt2); // rotation about "1" axis
RealTensorValue rtv2(1, 0, 0, 0, sqrt2, -sqrt2, 0, sqrt2, sqrt2); // rotation about "2" axis
RankTwoTensor rot0(rtv0);
RankTwoTensor rot0T = rot0.transpose();
RankTwoTensor rot1(rtv1);
RankTwoTensor rot1T = rot1.transpose();
RankTwoTensor rot2(rtv2);
RankTwoTensor rot2T = rot2.transpose();
RankTwoTensor rot = rot0*rot1*rot2;
RankTwoTensor answer;
RankTwoTensor m3;
// the following "answer"s come from mathematica of course!
// rotate about "0" axis with RealTensorValue, then back again with RankTwoTensor
m3 = _m3;
answer = RankTwoTensor(-4, 3, 6.363961, 3, 0, -2.1213403, 6.363961, -2.1213403, 9);
m3.rotate(rtv0);
CPPUNIT_ASSERT_DOUBLES_EQUAL(0, (m3 - answer).L2norm(), 0.0001);
m3.rotate(rot0T);
CPPUNIT_ASSERT_DOUBLES_EQUAL(0, (m3 - _m3).L2norm(), 0.0001);
// rotate about "1" axis with RealTensorValue, then back again with RankTwoTensor
m3 = _m3;
answer = RankTwoTensor(2, 5.656854, -4, 5.656854, -5, -2.828427, -4, -2.828427, 8);
m3.rotate(rtv1);
CPPUNIT_ASSERT_DOUBLES_EQUAL(0, (m3 - answer).L2norm(), 0.0001);
m3.rotate(rot1T);
CPPUNIT_ASSERT_DOUBLES_EQUAL(0, (m3 - _m3).L2norm(), 0.0001);
// rotate about "2" axis with RealTensorValue, then back again with RankTwoTensor
m3 = _m3;
answer = RankTwoTensor(1, -sqrt2, 3.5355339, -sqrt2, 8, -7, 3.5355339, -7, -4);
m3.rotate(rtv2);
CPPUNIT_ASSERT_DOUBLES_EQUAL(0, (m3 - answer).L2norm(), 0.0001);
m3.rotate(rot2T);
CPPUNIT_ASSERT_DOUBLES_EQUAL(0, (m3 - _m3).L2norm(), 0.0001);
// rotate with "rot"
m3 = _m3;
answer = RankTwoTensor(-2.9675144, -6.51776695, 5.6213203, -6.51776695, 5.9319805, -2.0857864, 5.6213203, -2.0857864, 2.0355339);
m3.rotate(rot);
CPPUNIT_ASSERT_DOUBLES_EQUAL(0, (m3 - answer).L2norm(), 0.0001);
}
RankTwoTensor
TensorMechanicsPlasticMeanCapTC::dflowPotential_dintnl(const RankTwoTensor & stress, Real intnl) const
{
const Real tr = stress.trace();
const Real t_str = tensile_strength(intnl);
if (tr >= t_str)
return RankTwoTensor();
const Real c_str = compressive_strength(intnl);
if (tr <= c_str)
return RankTwoTensor();
const Real dt = dtensile_strength(intnl);
const Real dc = dcompressive_strength(intnl);
return std::sin(M_PI * (tr - c_str) / (t_str - c_str)) * stress.dtrace() * M_PI / std::pow(t_str - c_str, 2) * ((tr - t_str) * dc - (tr - c_str) * dt);
}
RankTwoEigenRoutinesTest::RankTwoEigenRoutinesTest()
{
_m0 = RankTwoTensor(0, 0, 0, 0, 0, 0, 0, 0, 0);
_m1 = RankTwoTensor(1, 0, 0, 0, 1, 0, 0, 0, 1);
_m2 = RankTwoTensor(1, 0, 0, 0, 2, 0, 0, 0, 3);
_m3 = RankTwoTensor(1, 2, 3, 2, -5, -6, 3, -6, 9);
_m4 = RankTwoTensor(1, 0, 0, 0, 3, 0, 0, 0, 2);
_m5 = RankTwoTensor(1, 0, 0, 0, 1, 0, 0, 0, 2);
_m6 = RankTwoTensor(1, 0, 0, 0, 2, 0, 0, 0, 1);
_m7 = RankTwoTensor(1, 0, 0, 0, 2, 0, 0, 0, 2);
_m8 = RankTwoTensor(1, 1, 0, 1, 1, 0, 0, 0, 2); // has eigenvalues 0, 2 and 2
}
void
MultiPlasticityDebugger::fddyieldFunction_dstress(const RankTwoTensor & stress,
const std::vector<Real> & intnl,
std::vector<RankTwoTensor> & df_dstress)
{
df_dstress.assign(_num_surfaces, RankTwoTensor());
std::vector<bool> act;
act.assign(_num_surfaces, true);
Real ep = _fspb_debug_stress_change;
RankTwoTensor stressep;
std::vector<Real> fep, fep_minus;
for (unsigned i = 0; i < 3; ++i)
for (unsigned j = 0; j < 3; ++j)
{
stressep = stress;
// do a central difference to attempt to capture discontinuities
// such as those encountered in tensile and Mohr-Coulomb
stressep(i, j) += ep / 2.0;
yieldFunction(stressep, intnl, act, fep);
stressep(i, j) -= ep;
yieldFunction(stressep, intnl, act, fep_minus);
for (unsigned surface = 0; surface < _num_surfaces; ++surface)
df_dstress[surface](i, j) = (fep[surface] - fep_minus[surface]) / ep;
}
}
void
FiniteStrainPlasticBase::fddflowPotential_dintnl(const RankTwoTensor & stress, const std::vector<Real> & intnl, std::vector<std::vector<RankTwoTensor> > & dr_dintnl)
{
dr_dintnl.resize(numberOfYieldFunctions());
for (unsigned alpha = 0 ; alpha < numberOfYieldFunctions() ; ++alpha)
dr_dintnl[alpha].assign(numberOfInternalParameters(), RankTwoTensor());
std::vector<RankTwoTensor> origr;
flowPotential(stress, intnl, origr);
std::vector<Real> intnlep;
intnlep.resize(numberOfInternalParameters());
for (unsigned a = 0 ; a < numberOfInternalParameters() ; ++a)
intnlep[a] = intnl[a];
Real ep;
std::vector<RankTwoTensor> rep;
for (unsigned a = 0 ; a < numberOfInternalParameters() ; ++a)
{
ep = _fspb_debug_intnl_change[a];
intnlep[a] += ep;
flowPotential(stress, intnlep, rep);
for (unsigned alpha = 0 ; alpha < numberOfYieldFunctions() ; ++alpha)
dr_dintnl[alpha][a] = (rep[alpha] - origr[alpha])/ep;
intnlep[a] -= ep;
}
}
void
FiniteStrainPlasticBase::calculateConstraints(const RankTwoTensor & stress, const std::vector<Real> & intnl_old, const std::vector<Real> & intnl, const std::vector<Real> & pm, const RankTwoTensor & delta_dp, std::vector<Real> & f, RankTwoTensor & epp, std::vector<Real> & ic)
{
// yield functions
yieldFunction(stress, intnl, f);
// flow direction
std::vector<RankTwoTensor> r;
flowPotential(stress, intnl, r);
epp = RankTwoTensor();
for (unsigned alpha = 0 ; alpha < numberOfYieldFunctions() ; ++alpha)
epp += pm[alpha]*r[alpha];
epp -= delta_dp;
// internal constraints
std::vector<std::vector<Real> > h;
hardPotential(stress, intnl, h);
ic.resize(numberOfInternalParameters());
for (unsigned a = 0 ; a < numberOfInternalParameters() ; ++a)
{
ic[a] = intnl[a] - intnl_old[a];
for (unsigned alpha = 0 ; alpha < numberOfYieldFunctions() ; ++alpha)
ic[a] += pm[alpha]*h[a][alpha];
}
}
void
MultiPlasticityLinearSystem::calculateConstraints(const RankTwoTensor & stress,
const std::vector<Real> & intnl_old,
const std::vector<Real> & intnl,
const std::vector<Real> & pm,
const RankTwoTensor & delta_dp,
std::vector<Real> & f,
std::vector<RankTwoTensor> & r,
RankTwoTensor & epp,
std::vector<Real> & ic,
const std::vector<bool> & active)
{
// see comments at the start of .h file
mooseAssert(intnl_old.size() == _num_models,
"Size of intnl_old is " << intnl_old.size()
<< " which is incorrect in calculateConstraints");
mooseAssert(intnl.size() == _num_models,
"Size of intnl is " << intnl.size() << " which is incorrect in calculateConstraints");
mooseAssert(pm.size() == _num_surfaces,
"Size of pm is " << pm.size() << " which is incorrect in calculateConstraints");
mooseAssert(active.size() == _num_surfaces,
"Size of active is " << active.size()
<< " which is incorrect in calculateConstraints");
// yield functions
yieldFunction(stress, intnl, active, f);
// flow directions and "epp"
flowPotential(stress, intnl, active, r);
epp = RankTwoTensor();
unsigned ind = 0;
for (unsigned surface = 0; surface < _num_surfaces; ++surface)
if (active[surface])
epp += pm[surface] * r[ind++]; // note, even the deactivated_due_to_ld must get added in
epp -= delta_dp;
// internal constraints
std::vector<Real> h;
hardPotential(stress, intnl, active, h);
ic.resize(0);
ind = 0;
std::vector<unsigned int> active_surfaces;
std::vector<unsigned int>::iterator active_surface;
for (unsigned model = 0; model < _num_models; ++model)
{
activeSurfaces(model, active, active_surfaces);
if (active_surfaces.size() > 0)
{
// some surfaces are active in this model, so must form an internal constraint
ic.push_back(intnl[model] - intnl_old[model]);
for (active_surface = active_surfaces.begin(); active_surface != active_surfaces.end();
++active_surface)
ic[ic.size() - 1] += pm[*active_surface] * h[ind++]; // we know the correct one is h[ind]
// since it was constructed in the same
// manner
}
}
}
RankTwoTensor
TensorMechanicsPlasticJ2::dyieldFunction_dstress(const RankTwoTensor & stress, Real /*intnl*/) const
{
Real sII = stress.secondInvariant();
if (sII == 0.0)
return RankTwoTensor();
else
return 0.5 * std::sqrt(3.0 / sII) * stress.dsecondInvariant();
}
RankTwoTensor
RankTwoTensor::dsin3Lode(const Real r0) const
{
Real bar = secondInvariant();
if (bar <= r0)
return RankTwoTensor();
else
return -1.5 * std::sqrt(3.0) * (dthirdInvariant() / std::pow(bar, 1.5) - 1.5 * dsecondInvariant() * thirdInvariant() / std::pow(bar, 2.5));
}
void
GolemMaterialH::computeQpProperties()
{
_scaling_factor[_qp] = computeQpScaling();
_fluid_density[_qp] = _fluid_density_uo->computeDensity(0.0, 0.0, _rho0_f);
_fluid_viscosity[_qp] = _fluid_viscosity_uo->computeViscosity(0.0, 0.0, _mu0);
_porosity[_qp] = _porosity_uo->computePorosity(_phi0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0);
_permeability[_qp] =
_permeability_uo->computePermeability(_k0, _phi0, _porosity[_qp], _scaling_factor[_qp]);
GolemPropertiesH();
if (_has_disp)
{
// Declare some property when this material is used for fractures or faults in a HM simulation
(*_dH_kernel_dev)[_qp] = RankTwoTensor();
(*_dH_kernel_dpf)[_qp] = RankTwoTensor();
if (_fe_problem.isTransient())
{
(*_dH_kernel_time_dev)[_qp] = 0.0;
(*_dH_kernel_time_dpf)[_qp] = 0.0;
}
}
}
RankTwoTensorTest::RankTwoTensorTest()
{
_m0 = RankTwoTensor(0, 0, 0, 0, 0, 0, 0, 0, 0);
_m1 = RankTwoTensor(1, 0, 0, 0, 1, 0, 0, 0, 1);
_m2 = RankTwoTensor(1, 0, 0, 0, 2, 0, 0, 0, 3);
_m3 = RankTwoTensor(1, 2, 3, 2, -5, -6, 3, -6, 9);
_unsymmetric0 = RankTwoTensor(1, 2, 3, -4, -5, -6, 7, 8, 9);
_unsymmetric1 = RankTwoTensor(1, 2, 3, -4, -5, -6, 7, 8, 10);
}
void
CosseratLinearElasticMaterial::computeQpStrain()
{
RankTwoTensor strain(_grad_disp_x[_qp], _grad_disp_y[_qp], _grad_disp_z[_qp]);
RealVectorValue wc_vector((*_wc[0])[_qp], (*_wc[1])[_qp], (*_wc[2])[_qp]);
for (unsigned i = 0; i < LIBMESH_DIM; ++i)
for (unsigned j = 0; j < LIBMESH_DIM; ++j)
for (unsigned k = 0; k < LIBMESH_DIM; ++k)
strain(i, j) += PermutationTensor::eps(i, j, k) * wc_vector(k);
_elastic_strain[_qp] = strain;
_curvature[_qp] = RankTwoTensor((*_grad_wc[0])[_qp], (*_grad_wc[1])[_qp], (*_grad_wc[2])[_qp]);
}
RankTwoTensor
ComputeCappedWeakPlaneCosseratStress::dqdstress(const RankTwoTensor & stress) const
{
RankTwoTensor deriv = RankTwoTensor();
const Real q = std::sqrt(Utility::pow<2>(stress(0, 2)) + Utility::pow<2>(stress(1, 2)));
if (q > 0.0)
{
deriv(0, 2) = stress(0, 2) / q;
deriv(1, 2) = stress(1, 2) / q;
}
else
{
// derivative is not defined here. For now i'll set:
deriv(0, 2) = 1.0;
deriv(1, 2) = 1.0;
}
return deriv;
}
TensorMechanicsPlasticWeakPlaneTensileN::TensorMechanicsPlasticWeakPlaneTensileN(const InputParameters & parameters) :
TensorMechanicsPlasticWeakPlaneTensile(parameters),
_input_n(getParam<RealVectorValue>("normal_vector")),
_df_dsig(RankTwoTensor())
{
// cannot check the following for all values of strength, but this is a start
if (_strength.value(0) < 0)
mooseError("Weak plane tensile strength must not be negative");
if (_input_n.size() == 0)
mooseError("Weak-plane normal vector must not have zero length");
else
_input_n /= _input_n.size();
_rot = RotationMatrix::rotVecToZ(_input_n);
for (unsigned i = 0 ; i < 3 ; ++i)
for (unsigned j = 0 ; j < 3 ; ++j)
_df_dsig(i, j) = _rot(2, i)*_rot(2, j);
}
void
ComputeCosseratSmallStrain::computeQpProperties()
{
RankTwoTensor strain((*_grad_disp[0])[_qp], (*_grad_disp[1])[_qp], (*_grad_disp[2])[_qp]);
RealVectorValue wc_vector((*_wc[0])[_qp], (*_wc[1])[_qp], (*_wc[2])[_qp]);
for (unsigned i = 0; i < LIBMESH_DIM; ++i)
for (unsigned j = 0; j < LIBMESH_DIM; ++j)
for (unsigned k = 0; k < LIBMESH_DIM; ++k)
strain(i, j) += PermutationTensor::eps(i, j, k) * wc_vector(k);
_total_strain[_qp] = strain;
_mechanical_strain[_qp] = strain;
for (auto es : _eigenstrains)
_mechanical_strain[_qp] -= (*es)[_qp];
_curvature[_qp] = RankTwoTensor((*_grad_wc[0])[_qp], (*_grad_wc[1])[_qp], (*_grad_wc[2])[_qp]);
}
void
CappedDruckerPragerCosseratStressUpdate::setStressAfterReturn(const RankTwoTensor & stress_trial,
Real p_ok,
Real q_ok,
Real /*gaE*/,
const std::vector<Real> & /*intnl*/,
const yieldAndFlow & /*smoothed_q*/,
const RankFourTensor & /*Eijkl*/,
RankTwoTensor & stress) const
{
// symm_stress is the symmetric part of the stress tensor.
// symm_stress = (s_ij+s_ji)/2 + de_ij tr(stress) / 3
// = q / q_trial * (s_ij^trial+s_ji^trial)/2 + de_ij p / 3
// = q / q_trial * (symm_stress_ij^trial - de_ij tr(stress^trial) / 3) + de_ij p / 3
const Real p_trial = stress_trial.trace();
RankTwoTensor symm_stress = RankTwoTensor(RankTwoTensor::initIdentity) / 3.0 *
(p_ok - (_in_q_trial == 0.0 ? 0.0 : p_trial * q_ok / _in_q_trial));
if (_in_q_trial > 0)
symm_stress += q_ok / _in_q_trial * 0.5 * (stress_trial + stress_trial.transpose());
stress = symm_stress + 0.5 * (stress_trial - stress_trial.transpose());
}
void
FiniteStrainPlasticBase::fddyieldFunction_dstress(const RankTwoTensor & stress, const std::vector<Real> & intnl, std::vector<RankTwoTensor> & df_dstress)
{
df_dstress.assign(numberOfYieldFunctions(), RankTwoTensor());
Real ep = _fspb_debug_stress_change;
RankTwoTensor stressep;
std::vector<Real> fep, fep_minus;
for (unsigned i = 0 ; i < 3 ; ++i)
for (unsigned j = 0 ; j < 3 ; ++j)
{
stressep = stress;
// do a central difference to attempt to capture discontinuities
// such as those encountered in tensile and Mohr-Coulomb
stressep(i, j) += ep/2.0;
yieldFunction(stressep, intnl, fep);
stressep(i, j) -= ep;
yieldFunction(stressep, intnl, fep_minus);
for (unsigned alpha = 0 ; alpha < numberOfYieldFunctions() ; ++alpha)
df_dstress[alpha](i, j) = (fep[alpha] - fep_minus[alpha])/ep;
}
}
RankTwoTensor
TensorMechanicsPlasticTensile::dflowPotential_dintnl(const RankTwoTensor & /*stress*/,
Real /*intnl*/) const
{
return RankTwoTensor();
}
RankTwoTensor
TensorMechanicsPlasticModel::dhardPotential_dstress(const RankTwoTensor & /*stress*/, Real /*intnl*/) const
{
return RankTwoTensor();
}
bool
TensorMechanicsPlasticMohrCoulombMulti::doReturnMap(const RankTwoTensor & trial_stress, Real intnl_old, const RankFourTensor & E_ijkl,
Real ep_plastic_tolerance, RankTwoTensor & returned_stress, Real & returned_intnl,
std::vector<Real> & dpm, RankTwoTensor & delta_dp, std::vector<Real> & yf,
bool & trial_stress_inadmissible) const
{
mooseAssert(dpm.size() == 6, "TensorMechanicsPlasticMohrCoulombMulti size of dpm should be 6 but it is " << dpm.size());
std::vector<Real> eigvals;
RankTwoTensor eigvecs;
trial_stress.symmetricEigenvaluesEigenvectors(eigvals, eigvecs);
eigvals[0] += _shift;
eigvals[2] -= _shift;
Real sinphi = std::sin(phi(intnl_old));
Real cosphi = std::cos(phi(intnl_old));
Real coh = cohesion(intnl_old);
Real cohcos = coh*cosphi;
yieldFunctionEigvals(eigvals[0], eigvals[1], eigvals[2], sinphi, cohcos, yf);
if (yf[0] <= _f_tol && yf[1] <= _f_tol && yf[2] <= _f_tol && yf[3] <= _f_tol && yf[4] <= _f_tol && yf[5] <= _f_tol)
{
// purely elastic (trial_stress, intnl_old)
trial_stress_inadmissible = false;
return true;
}
trial_stress_inadmissible = true;
delta_dp.zero();
returned_stress = RankTwoTensor();
// these are the normals to the 6 yield surfaces, which are const because of the assumption of no psi hardening
std::vector<RealVectorValue> norm(6);
const Real sinpsi = std::sin(psi(intnl_old));
const Real oneminus = 0.5*(1 - sinpsi);
const Real oneplus = 0.5*(1 + sinpsi);
norm[0](0) = oneplus; norm[0](1) = -oneminus; norm[0](2) = 0;
norm[1](0) = -oneminus; norm[1](1) = oneplus; norm[1](2) = 0;
norm[2](0) = oneplus; norm[2](1) = 0; norm[2](2) = -oneminus;
norm[3](0) = -oneminus; norm[3](1) = 0; norm[3](2) = oneplus;
norm[4](0) = 0; norm[4](1) = oneplus; norm[4](2) = -oneminus;
norm[5](0) = 0; norm[5](1) = -oneminus; norm[5](2) = oneplus;
// the flow directions are these norm multiplied by Eijkl.
// I call the flow directions "n".
// In the following I assume that the Eijkl is
// for an isotropic situation. Then I don't have to
// rotate to the principal-stress frame, and i don't
// have to worry about strange off-diagonal things
std::vector<RealVectorValue> n(6);
for (unsigned ys = 0; ys < 6; ++ys)
for (unsigned i = 0; i < 3; ++i)
for (unsigned j = 0; j < 3; ++j)
n[ys](i) += E_ijkl(i,i,j,j)*norm[ys](j);
const Real mag_E = E_ijkl(0, 0, 0, 0);
// With non-zero Poisson's ratio and hardening
// it is not computationally cheap to know whether
// the trial stress will return to the tip, edge,
// or plane. The following at least
// gives a not-completely-stupid guess
// trial_order[0] = type of return to try first
// trial_order[1] = type of return to try second
// trial_order[2] = type of return to try third
// trial_order[3] = type of return to try fourth
// trial_order[4] = type of return to try fifth
// In the following the "binary" stuff indicates the
// deactive (0) and active (1) surfaces, eg
// 110100 means that surfaces 0, 1 and 3 are active
// and 2, 4 and 5 are deactive
const unsigned int number_of_return_paths = 5;
std::vector<int> trial_order(number_of_return_paths);
if (yf[1] > _f_tol && yf[3] > _f_tol && yf[5] > _f_tol)
{
trial_order[0] = tip110100;
trial_order[1] = edge010100;
trial_order[2] = plane000100;
trial_order[3] = edge000101;
trial_order[4] = tip010101;
}
else if (yf[1] <= _f_tol && yf[3] > _f_tol && yf[5] > _f_tol)
{
trial_order[0] = edge000101;
trial_order[1] = plane000100;
trial_order[2] = tip110100;
trial_order[3] = tip010101;
trial_order[4] = edge010100;
}
else if (yf[1] <= _f_tol && yf[3] > _f_tol && yf[5] <= _f_tol)
{
trial_order[0] = plane000100;
trial_order[1] = edge000101;
trial_order[2] = edge010100;
trial_order[3] = tip110100;
trial_order[4] = tip010101;
}
else
{
trial_order[0] = edge010100;
trial_order[1] = plane000100;
trial_order[2] = edge000101;
trial_order[3] = tip110100;
trial_order[4] = tip010101;
}
unsigned trial;
bool nr_converged = false;
bool kt_success = false;
std::vector<RealVectorValue> ntip(3);
std::vector<Real> dpmtip(3);
for (trial = 0; trial < number_of_return_paths; ++trial)
{
switch (trial_order[trial])
{
case tip110100:
for (unsigned int i = 0; i < 3; ++i)
{
ntip[0](i) = n[0](i);
ntip[1](i) = n[1](i);
ntip[2](i) = n[3](i);
}
kt_success = returnTip(eigvals, ntip, dpmtip, returned_stress, intnl_old, sinphi, cohcos, 0, nr_converged, ep_plastic_tolerance, yf);
if (nr_converged && kt_success)
{
dpm[0] = dpmtip[0];
dpm[1] = dpmtip[1];
dpm[3] = dpmtip[2];
dpm[2] = dpm[4] = dpm[5] = 0;
}
break;
case tip010101:
for (unsigned int i = 0; i < 3; ++i)
{
ntip[0](i) = n[1](i);
ntip[1](i) = n[3](i);
ntip[2](i) = n[5](i);
}
kt_success = returnTip(eigvals, ntip, dpmtip, returned_stress, intnl_old, sinphi, cohcos, 0, nr_converged, ep_plastic_tolerance, yf);
if (nr_converged && kt_success)
{
dpm[1] = dpmtip[0];
dpm[3] = dpmtip[1];
dpm[5] = dpmtip[2];
dpm[0] = dpm[2] = dpm[4] = 0;
}
break;
case edge000101:
kt_success = returnEdge000101(eigvals, n, dpm, returned_stress, intnl_old, sinphi, cohcos, 0, mag_E, nr_converged, ep_plastic_tolerance, yf);
break;
case edge010100:
kt_success = returnEdge010100(eigvals, n, dpm, returned_stress, intnl_old, sinphi, cohcos, 0, mag_E, nr_converged, ep_plastic_tolerance, yf);
break;
case plane000100:
kt_success = returnPlane(eigvals, n, dpm, returned_stress, intnl_old, sinphi, cohcos, 0, nr_converged, ep_plastic_tolerance, yf);
break;
}
if (nr_converged && kt_success)
break;
}
if (trial == number_of_return_paths)
{
sinphi = std::sin(phi(intnl_old));
cosphi = std::cos(phi(intnl_old));
coh = cohesion(intnl_old);
cohcos = coh*cosphi;
yieldFunctionEigvals(eigvals[0], eigvals[1], eigvals[2], sinphi, cohcos, yf);
Moose::err << "Trial stress = \n";
trial_stress.print(Moose::err);
Moose::err << "which has eigenvalues = " << eigvals[0] << " " << eigvals[1] << " " << eigvals[2] << "\n";
Moose::err << "and yield functions = " << yf[0] << " " << yf[1] << " " << yf[2] << " " << yf[3] << " " << yf[4] << " " << yf[5] << "\n";
Moose::err << "Internal parameter = " << intnl_old << "\n";
mooseError("TensorMechanicsPlasticMohrCoulombMulti: FAILURE! You probably need to implement a line search if your hardening is too severe, or you need to tune your tolerances (eg, yield_function_tolerance should be a little smaller than (young modulus)*ep_plastic_tolerance).\n");
return false;
}
// success
returned_intnl = intnl_old;
for (unsigned i = 0; i < 6; ++i)
returned_intnl += dpm[i];
for (unsigned i = 0; i < 6; ++i)
for (unsigned j = 0; j < 3; ++j)
delta_dp(j, j) += dpm[i]*norm[i](j);
returned_stress = eigvecs*returned_stress*(eigvecs.transpose());
delta_dp = eigvecs*delta_dp*(eigvecs.transpose());
return true;
}
void
CappedDruckerPragerCosseratStressUpdate::consistentTangentOperator(
const RankTwoTensor & /*stress_trial*/,
Real /*p_trial*/,
Real /*q_trial*/,
const RankTwoTensor & stress,
Real /*p*/,
Real q,
Real gaE,
const yieldAndFlow & smoothed_q,
const RankFourTensor & Eijkl,
bool compute_full_tangent_operator,
RankFourTensor & cto) const
{
if (!compute_full_tangent_operator)
{
cto = Eijkl;
return;
}
RankFourTensor EAijkl;
for (unsigned i = 0; i < _tensor_dimensionality; ++i)
for (unsigned j = 0; j < _tensor_dimensionality; ++j)
for (unsigned k = 0; k < _tensor_dimensionality; ++k)
for (unsigned l = 0; l < _tensor_dimensionality; ++l)
{
cto(i, j, k, l) = 0.5 * (Eijkl(i, j, k, l) + Eijkl(j, i, k, l));
EAijkl(i, j, k, l) = 0.5 * (Eijkl(i, j, k, l) - Eijkl(j, i, k, l));
}
const RankTwoTensor s_over_q =
(q == 0.0 ? RankTwoTensor()
: (0.5 * (stress + stress.transpose()) -
stress.trace() * RankTwoTensor(RankTwoTensor::initIdentity) / 3.0) /
q);
const RankTwoTensor E_s_over_q = Eijkl.innerProductTranspose(s_over_q); // not symmetric in kl
const RankTwoTensor Ekl =
RankTwoTensor(RankTwoTensor::initIdentity).initialContraction(Eijkl); // symmetric in kl
for (unsigned i = 0; i < _tensor_dimensionality; ++i)
for (unsigned j = 0; j < _tensor_dimensionality; ++j)
for (unsigned k = 0; k < _tensor_dimensionality; ++k)
for (unsigned l = 0; l < _tensor_dimensionality; ++l)
{
cto(i, j, k, l) -= (i == j) * (1.0 / 3.0) *
(Ekl(k, l) * (1.0 - _dp_dpt) + 0.5 * E_s_over_q(k, l) * (-_dp_dqt));
cto(i, j, k, l) -=
s_over_q(i, j) * (Ekl(k, l) * (-_dq_dpt) + 0.5 * E_s_over_q(k, l) * (1.0 - _dq_dqt));
}
if (smoothed_q.dg[1] != 0.0)
{
const RankFourTensor Tijab = _Ehost * (gaE / _Epp) * smoothed_q.dg[1] * d2qdstress2(stress);
RankFourTensor inv = RankFourTensor(RankFourTensor::initIdentitySymmetricFour) + Tijab;
try
{
inv = inv.transposeMajor().invSymm();
}
catch (const MooseException & e)
{
// Cannot form the inverse, so probably at some degenerate place in stress space.
// Just return with the "best estimate" of the cto.
mooseWarning("CappedDruckerPragerCosseratStressUpdate: Cannot invert 1+T in consistent "
"tangent operator computation at quadpoint ",
_qp,
" of element ",
_current_elem->id());
return;
}
cto = (cto.transposeMajor() * inv).transposeMajor();
}
cto += EAijkl;
}
void
TensorMechanicsPlasticTensileMulti::dflowPotential_dintnlV(const RankTwoTensor & /*stress*/, const Real & /*intnl*/, std::vector<RankTwoTensor> & dr_dintnl) const
{
dr_dintnl.assign(3, RankTwoTensor());
}
void
TensorMechanicsPlasticTensileMulti::activeConstraints(const std::vector<Real> & f, const RankTwoTensor & stress, const Real & intnl, const RankFourTensor & Eijkl, std::vector<bool> & act, RankTwoTensor & returned_stress) const
{
act.assign(3, false);
if (f[0] <= _f_tol && f[1] <= _f_tol && f[2] <= _f_tol)
{
returned_stress = stress;
return;
}
returned_stress = RankTwoTensor();
std::vector<Real> eigvals;
RankTwoTensor eigvecs;
stress.symmetricEigenvaluesEigenvectors(eigvals, eigvecs);
eigvals[0] += _shift;
eigvals[2] -= _shift;
Real str = tensile_strength(intnl);
std::vector<Real> v(3);
v[0] = eigvals[0] - str;
v[1] = eigvals[1] - str;
v[2] = eigvals[2] - str;
// these are the normals to the 3 yield surfaces
std::vector<std::vector<Real> > n(3);
n[0].resize(3);
n[0][0] = 1 ; n[0][1] = 0 ; n[0][2] = 0;
n[1].resize(3);
n[1][0] = 0 ; n[1][1] = 1 ; n[1][2] = 0;
n[2].resize(3);
n[2][0] = 0 ; n[2][1] = 0 ; n[2][2] = 1;
// the flow directions are these n multiplied by Eijkl.
// I re-use the name "n" for the flow directions
// In the following I assume that the Eijkl is
// for an isotropic situation. This is the most
// common when using TensileMulti, and remember
// that the returned_stress need not be perfect
// anyway.
// I divide by E(0,0,0,0) so the n remain of order 1
Real ratio = Eijkl(1,1,0,0)/Eijkl(0,0,0,0);
n[0][1] = n[0][2] = ratio;
n[1][0] = n[1][2] = ratio;
n[2][0] = n[2][1] = ratio;
// 111 (tip)
// For tip-return to satisfy Kuhn-Tucker, we need
// v = alpha*n[0] + beta*n[1] * gamma*n[2]
// with alpha, beta, and gamma all being non-negative (they are
// the plasticity multipliers)
Real denom = triple(n[0], n[1], n[2]);
if (triple(v, n[0], n[1])/denom >= 0 && triple(v, n[1], n[2])/denom >= 0 && triple(v, n[2], n[0])/denom >= 0)
{
act[0] = act[1] = act[2] = true;
returned_stress(0, 0) = returned_stress(1, 1) = returned_stress(2, 2) = str;
returned_stress = eigvecs*returned_stress*(eigvecs.transpose());
return;
}
// 011 (edge)
std::vector<Real> n1xn2(3);
n1xn2[0] = n[1][1]*n[2][2] - n[1][2]*n[2][1];
n1xn2[1] = n[1][2]*n[2][0] - n[1][0]*n[2][2];
n1xn2[2] = n[1][0]*n[2][1] - n[1][1]*n[2][0];
// work out the point to which we would return, "a". It is defined by
// f1 = 0 = f2, and that (p - a).(n1 x n2) = 0, where "p" is the
// starting position (p = eigvals).
// In the following a = (a0, str, str)
Real pdotn1xn2 = dot(eigvals, n1xn2);
Real a0 = (-str*n1xn2[1] - str*n1xn2[2] + pdotn1xn2)/n1xn2[0];
// we need p - a = alpha*n1 + beta*n2, where alpha and beta are non-negative
// for Kuhn-Tucker to be satisfied
std::vector<Real> pminusa(3);
pminusa[0] = eigvals[0] - a0;
pminusa[1] = v[1];
pminusa[2] = v[2];
if ((pminusa[2] - pminusa[0])/(1.0 - ratio) >= 0 && (pminusa[1] - pminusa[0])/(1.0 - ratio) >= 0)
{
returned_stress(0, 0) = a0;
returned_stress(1, 1) = str;
returned_stress(2, 2) = str;
returned_stress = eigvecs*returned_stress*(eigvecs.transpose());
act[1] = act[2] = true;
return;
}
// 001 (plane)
// the returned point, "a", is defined by f2=0 and
// a = p - alpha*n2
Real alpha = (eigvals[2] - str)/n[2][2];
act[2] = true;
returned_stress(0, 0) = eigvals[0] - alpha*n[2][0];
returned_stress(1, 1) = eigvals[1] - alpha*n[2][1];
returned_stress(2, 2) = str;
returned_stress = eigvecs*returned_stress*(eigvecs.transpose());
return;
}
RankTwoTensor
TensorMechanicsPlasticSimpleTester::dflowPotential_dintnl(const RankTwoTensor & /*stress*/, const Real & /*intnl*/) const
{
return RankTwoTensor();
}
void
GolemMaterialTH::computeQpProperties()
{
if (_has_lumped_mass_matrix)
{
(*_node_number)[_qp] = nearest();
(*_nodal_temp)[_qp] = (*_nodal_temp_var)[(*_node_number)[_qp]];
(*_nodal_temp_old)[_qp] = (*_nodal_temp_var_old)[(*_node_number)[_qp]];
(*_nodal_pf)[_qp] = (*_nodal_pf_var)[(*_node_number)[_qp]];
if (_has_boussinesq)
(*_nodal_pf_old)[_qp] = (*_nodal_pf_var_old)[(*_node_number)[_qp]];
}
_scaling_factor[_qp] = computeQpScaling();
computeDensity();
computeViscosity();
_porosity[_qp] = _porosity_uo->computePorosity(_phi0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0);
_permeability[_qp] =
_permeability_uo->computePermeability(_k0, _phi0, _porosity[_qp], _scaling_factor[_qp]);
// GolemKernelT related properties
_T_kernel_diff[_qp] = _porosity[_qp] * _lambda_f + (1.0 - _porosity[_qp]) * _lambda_s;
if (_has_T_source_sink)
(*_T_kernel_source)[_qp] = -1.0 * _T_source_sink;
// GolemKernelH related properties
GolemPropertiesH();
// GolemkernelTH related poperties
_TH_kernel[_qp] = -_H_kernel[_qp] * _fluid_density[_qp] * _c_f;
if (_fe_problem.isTransient())
{
// Correct H_kernel_time
if (_drho_dpf[_qp] != 0.0)
(*_H_kernel_time)[_qp] = (_porosity[_qp] * _drho_dpf[_qp]) / _fluid_density[_qp];
(*_T_kernel_time)[_qp] =
_porosity[_qp] * _fluid_density[_qp] * _c_f + (1.0 - _porosity[_qp]) * _rho0_s * _c_s;
}
// Properties derivatives
// H_kernel derivatives
(*_dH_kernel_dpf)[_qp] = -_H_kernel[_qp] * _dmu_dpf[_qp] / _fluid_viscosity[_qp];
_dH_kernel_dT[_qp] = -_H_kernel[_qp] * _dmu_dT[_qp] / _fluid_viscosity[_qp];
// H_kernel_grav derivatives
_dH_kernel_grav_dpf[_qp] = -_drho_dpf[_qp] * _gravity;
_dH_kernel_grav_dT[_qp] = -_drho_dT[_qp] * _gravity;
if (_fe_problem.isTransient())
{
// T_kernel_time
(*_dT_kernel_time_dpf)[_qp] = _drho_dpf[_qp] * _porosity[_qp] * _c_f;
(*_dT_kernel_time_dT)[_qp] = _drho_dT[_qp] * _porosity[_qp] * _c_f;
}
// TH_kernel derivatives
_dTH_kernel_dpf[_qp] = -(_fluid_density[_qp] * _c_f * (*_dH_kernel_dpf)[_qp] +
_H_kernel[_qp] * _c_f * _drho_dpf[_qp]);
_dTH_kernel_dT[_qp] =
-(_fluid_density[_qp] * _c_f * _dH_kernel_dT[_qp] + _H_kernel[_qp] * _c_f * _drho_dT[_qp]);
if (_has_SUPG_upwind)
computeQpSUPG();
if (_has_disp)
{
// Declare some property when this material is used for fractures or faults in a THM simulation
(*_dH_kernel_dev)[_qp] = RankTwoTensor();
(*_dT_kernel_diff_dev)[_qp] = 0.0;
(*_dT_kernel_diff_dpf)[_qp] = 0.0;
(*_dT_kernel_diff_dT)[_qp] = 0.0;
if (_fe_problem.isTransient())
{
(*_dT_kernel_time_dev)[_qp] = 0.0;
(*_dH_kernel_time_dev)[_qp] = 0.0;
(*_dH_kernel_time_dpf)[_qp] = 0.0;
(*_dH_kernel_time_dT)[_qp] = 0.0;
}
}
}
RankTwoTensor
RankTwoTensor::dtrace() const
{
return RankTwoTensor(1, 0, 0, 0, 1, 0, 0, 0, 1);
}
RankTwoTensor
TensorMechanicsPlasticModel::dyieldFunction_dstress(const RankTwoTensor & /*stress*/, const Real & /*intnl*/) const
{
return RankTwoTensor();
}
void
MultiPlasticityLinearSystem::calculateJacobian(const RankTwoTensor & stress, const std::vector<Real> & intnl, const std::vector<Real> & pm, const RankFourTensor & E_inv, const std::vector<bool> & active, const std::vector<bool> & deactivated_due_to_ld, std::vector<std::vector<Real> > & jac)
{
// see comments at the start of .h file
mooseAssert(intnl.size() == _num_models, "Size of intnl is " << intnl.size() << " which is incorrect in calculateJacobian");
mooseAssert(pm.size() == _num_surfaces, "Size of pm is " << pm.size() << " which is incorrect in calculateJacobian");
mooseAssert(active.size() == _num_surfaces, "Size of active is " << active.size() << " which is incorrect in calculateJacobian");
mooseAssert(deactivated_due_to_ld.size() == _num_surfaces, "Size of deactivated_due_to_ld is " << deactivated_due_to_ld.size() << " which is incorrect in calculateJacobian");
unsigned ind = 0;
unsigned active_surface_ind = 0;
std::vector<bool> active_surface(_num_surfaces); // active and not deactivated_due_to_ld
for (unsigned surface = 0 ; surface < _num_surfaces ; ++surface)
active_surface[surface] = (active[surface] && !deactivated_due_to_ld[surface]);
unsigned num_active_surface = 0;
for (unsigned surface = 0 ; surface < _num_surfaces ; ++surface)
if (active_surface[surface])
num_active_surface++;
std::vector<bool> active_model(_num_models); // whether a model has surfaces that are active and not deactivated_due_to_ld
for (unsigned model = 0 ; model < _num_models ; ++model)
active_model[model] = anyActiveSurfaces(model, active_surface);
unsigned num_active_model = 0;
for (unsigned model = 0 ; model < _num_models ; ++model)
if (active_model[model])
num_active_model++;
ind = 0;
std::vector<unsigned int> active_model_index(_num_models);
for (unsigned model = 0 ; model < _num_models ; ++model)
if (active_model[model])
active_model_index[model] = ind++;
else
active_model_index[model] = _num_models+1; // just a dummy, that will probably cause a crash if something goes wrong
std::vector<RankTwoTensor> df_dstress;
dyieldFunction_dstress(stress, intnl, active_surface, df_dstress);
std::vector<Real> df_dintnl;
dyieldFunction_dintnl(stress, intnl, active_surface, df_dintnl);
std::vector<RankTwoTensor> r;
flowPotential(stress, intnl, active, r);
std::vector<RankFourTensor> dr_dstress;
dflowPotential_dstress(stress, intnl, active, dr_dstress);
std::vector<RankTwoTensor> dr_dintnl;
dflowPotential_dintnl(stress, intnl, active, dr_dintnl);
std::vector<Real> h;
hardPotential(stress, intnl, active, h);
std::vector<RankTwoTensor> dh_dstress;
dhardPotential_dstress(stress, intnl, active, dh_dstress);
std::vector<Real> dh_dintnl;
dhardPotential_dintnl(stress, intnl, active, dh_dintnl);
// d(epp)/dstress = sum_{active alpha} pm[alpha]*dr_dstress
RankFourTensor depp_dstress;
ind = 0;
for (unsigned surface = 0 ; surface < _num_surfaces ; ++surface)
if (active[surface]) // includes deactivated_due_to_ld
depp_dstress += pm[surface]*dr_dstress[ind++];
depp_dstress += E_inv;
// d(epp)/dpm_{active_surface_index} = r_{active_surface_index}
std::vector<RankTwoTensor> depp_dpm;
depp_dpm.resize(num_active_surface);
ind = 0;
active_surface_ind = 0;
for (unsigned surface = 0 ; surface < _num_surfaces ; ++surface)
{
if (active[surface])
{
if (active_surface[surface]) // do not include the deactived_due_to_ld, since their pm are not dofs in the NR
depp_dpm[active_surface_ind++] = r[ind];
ind++;
}
}
// d(epp)/dintnl_{active_model_index} = sum(pm[asdf]*dr_dintnl[fdsa])
std::vector<RankTwoTensor> depp_dintnl;
depp_dintnl.assign(num_active_model, RankTwoTensor());
ind = 0;
for (unsigned surface = 0 ; surface < _num_surfaces ; ++surface)
{
if (active[surface])
{
unsigned int model_num = modelNumber(surface);
if (active_model[model_num]) // only include models with surfaces which are still active after deactivated_due_to_ld
depp_dintnl[active_model_index[model_num]] += pm[surface]*dr_dintnl[ind];
ind++;
}
}
// df_dstress has been calculated above
// df_dpm is always zero
// df_dintnl has been calculated above, but only the active_surface+active_model stuff needs to be included in Jacobian: see below
std::vector<RankTwoTensor> dic_dstress;
dic_dstress.assign(num_active_model, RankTwoTensor());
ind = 0;
for (unsigned surface = 0 ; surface < _num_surfaces ; ++surface)
{
if (active[surface])
{
unsigned int model_num = modelNumber(surface);
if (active_model[model_num]) // only include ic for models with active_surface (ie, if model only contains deactivated_due_to_ld don't include it)
dic_dstress[active_model_index[model_num]] += pm[surface]*dh_dstress[ind];
ind++;
}
}
std::vector<std::vector<Real> > dic_dpm;
dic_dpm.resize(num_active_model);
ind = 0;
active_surface_ind = 0;
for (unsigned model = 0 ; model < num_active_model ; ++model)
dic_dpm[model].assign(num_active_surface, 0);
for (unsigned surface = 0 ; surface < _num_surfaces ; ++surface)
{
if (active[surface])
{
if (active_surface[surface]) // only take derivs wrt active-but-not-deactivated_due_to_ld pm
{
unsigned int model_num = modelNumber(surface);
// if (active_model[model_num]) // do not need this check as if the surface has active_surface, the model must be deemed active!
dic_dpm[active_model_index[model_num]][active_surface_ind] = h[ind];
active_surface_ind++;
}
ind++;
}
}
std::vector<std::vector<Real> > dic_dintnl;
dic_dintnl.resize(num_active_model);
for (unsigned model = 0 ; model < num_active_model ; ++model)
{
dic_dintnl[model].assign(num_active_model, 0);
dic_dintnl[model][model] = 1; // deriv wrt internal parameter
}
ind = 0;
for (unsigned surface = 0 ; surface < _num_surfaces ; ++surface)
{
if (active[surface])
{
unsigned int model_num = modelNumber(surface);
if (active_model[model_num]) // only the models that contain surfaces that are still active after deactivation_due_to_ld
dic_dintnl[active_model_index[model_num]][active_model_index[model_num]] += pm[surface]*dh_dintnl[ind];
ind++;
}
}
unsigned int dim = 3;
unsigned int system_size = 6 + num_active_surface + num_active_model; // "6" comes from symmeterizing epp
jac.resize(system_size);
for (unsigned i = 0 ; i < system_size ; ++i)
jac[i].assign(system_size, 0);
unsigned int row_num = 0;
unsigned int col_num = 0;
for (unsigned i = 0 ; i < dim ; ++i)
for (unsigned j = 0 ; j <= i ; ++j)
{
for (unsigned k = 0 ; k < dim ; ++k)
for (unsigned l = 0 ; l <= k ; ++l)
jac[col_num][row_num++] = depp_dstress(i, j, k, l) + (k != l ? depp_dstress(i, j, l, k) : 0); // extra part is needed because i assume dstress(i, j) = dstress(j, i)
for (unsigned surface = 0 ; surface < num_active_surface ; ++surface)
jac[col_num][row_num++] = depp_dpm[surface](i, j);
for (unsigned a = 0 ; a < num_active_model ; ++a)
jac[col_num][row_num++] = depp_dintnl[a](i, j);
row_num = 0;
col_num++;
}
ind = 0;
for (unsigned surface = 0 ; surface < _num_surfaces ; ++surface)
if (active_surface[surface])
{
for (unsigned k = 0 ; k < dim ; ++k)
for (unsigned l = 0 ; l <= k ; ++l)
jac[col_num][row_num++] = df_dstress[ind](k, l) + (k != l ? df_dstress[ind](l, k) : 0); // extra part is needed because i assume dstress(i, j) = dstress(j, i)
for (unsigned beta = 0 ; beta < num_active_surface ; ++beta)
jac[col_num][row_num++] = 0; // df_dpm
for (unsigned model = 0 ; model < _num_models ; ++model)
if (active_model[model]) // only use df_dintnl for models in active_model
{
if (modelNumber(surface) == model)
jac[col_num][row_num++] = df_dintnl[ind];
else
jac[col_num][row_num++] = 0;
}
ind++;
row_num = 0;
col_num++;
}
for (unsigned a = 0 ; a < num_active_model ; ++a)
{
for (unsigned k = 0 ; k < dim ; ++k)
for (unsigned l = 0 ; l <= k ; ++l)
jac[col_num][row_num++] = dic_dstress[a](k, l) + (k != l ? dic_dstress[a](l, k) : 0); // extra part is needed because i assume dstress(i, j) = dstress(j, i)
for (unsigned alpha = 0 ; alpha < num_active_surface ; ++alpha)
jac[col_num][row_num++] = dic_dpm[a][alpha];
for (unsigned b = 0 ; b < num_active_model ; ++b)
jac[col_num][row_num++] = dic_dintnl[a][b];
row_num = 0;
col_num++;
}
mooseAssert(col_num == system_size, "Incorrect filling of cols in Jacobian");
}
RankTwoTensor
TensorMechanicsPlasticModel::flowPotential(const RankTwoTensor & /*stress*/, const Real & /*intnl*/) const
{
return RankTwoTensor();
}