//********************************************************************** PHX_EVALUATE_FIELDS(Equations,workset) { for (int i=0; i < residual_temp.size(); ++i) residual_temp[i] = 0.0; for (int i=0; i < residual_vel.size(); ++i) residual_vel[i] = 0.0; std::vector<Element_Linear2D>::iterator element = workset.begin; for (std::size_t cell = 0; cell < workset.num_cells; ++cell,++element) { const Kokkos::View<double**,PHX::Device> phi = element->basisFunctions(); const Kokkos::View<double***,PHX::Device> grad_phi = element->basisFunctionGradientsRealSpace(); const Kokkos::View<double*,PHX::Device> det_jac = element->detJacobian(); const Kokkos::View<double*,PHX::Device> weights = element->quadratureWeights(); for (int node = 0; node < element->numNodes(); ++node) { for (int qp = 0; qp < num_qp; ++qp) { residual_temp(cell,node) += det_jac(qp) * weights(qp) * ( grad_phi(qp,node,0) * grad_temp(cell,qp,0) + grad_phi(qp,node,1) * grad_temp(cell,qp,1) + 1000.0 * phi(qp,node) * temp(cell,qp) * vel(cell,qp) ); residual_vel(cell,node) += det_jac(qp) * weights(qp) * ( grad_phi(qp,node,0) * grad_vel(cell,qp,0) + grad_phi(qp,node,1) * grad_vel(cell,qp,1) + 1000.0 * phi(qp,node) * temp(cell,qp) * vel(cell,qp) ); } } } // std::cout << "Temp Residual" << std::endl; // residual_temp.print(std::cout,true); // std::cout << "Vx Residual" << std::endl; // residual_vel.print(std::cout,true); }
KOKKOS_INLINE_FUNCTION void Fourier<EvalT, Traits>::operator () (const int i) const { for (PHX::index_size_type qp = 0; qp < num_qp; ++qp) for (PHX::index_size_type dim = 0; dim < num_dim; ++dim) flux(i,qp,dim) = - density(i,qp) * dc(i,qp) * grad_temp(i,qp,dim); }
void DataProcessing::computeGradient( const std::vector<double>& alt, const std::vector<double>& dist, std::vector<double>& grad) { assert(alt.size() == dist.size()); assert(alt.size() > 1); // Compute gradient from altitude const double grad_limit = 30.0; // define a max grad (incase of noise in signal) std::vector<double> grad_temp(alt.size()); for (unsigned int i=1; i < alt.size(); ++i) { if (dist[i] - dist[i-1] > 1.0) grad_temp[i] = std::min(std::max(100*(alt[i] - alt[i-1])/(dist[i] - dist[i-1]), -grad_limit),grad_limit); } grad.resize(alt.size()); DataProcessing::lowPassFilterSignal(grad_temp,grad,10); }