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Commit a127bf5a authored by Fanny CHOPOT's avatar Fanny CHOPOT
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Creation fichier essai 2

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src/scheme/FiniteVolumesDiffusion.hpp 0 → 100644
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#ifndef FINITE_VOLUMES_DIFFUSION_HPP
#define FINITE_VOLUMES_DIFFUSION_HPP
// --- INCLUSION fichiers headers ---
#include <Kokkos_Core.hpp>
#include <rang.hpp>
#include <BlockPerfectGas.hpp>
#include <TinyVector.hpp>
#include <TinyMatrix.hpp>
#include <Mesh.hpp>
#include <MeshData.hpp>
#include <FiniteVolumesEulerUnknowns.hpp>
// ---------------------------------
// Creation classe FiniteVolumesDiffusion
template<typename MeshData> // MeshData est le type generique des donnees (geometriques) attachees a un maillage
class FiniteVolumesDiffusion
{
typedef typename MeshData::MeshType MeshType; // de type du maillage
typedef FiniteVolumesEulerUnknowns<MeshData> UnknownsType; // type des inconnues
MeshData& m_mesh_data; //reference vers les donnees attachees du maillage
const MeshType& m_mesh; // reference vers le maillage
const typename MeshType::Connectivity& m_connectivity; // references vers la connectivite
constexpr static size_t dimension = MeshType::dimension; // dimension du maillage (connue a la compilation)
typedef TinyVector<dimension> Rd; // type de petits vecteurs (de dimension MeshType::dimension)
typedef TinyMatrix<dimension> Rdd; // type de petites matrices
private:
// Sert a calculer les reductions (en gros calculer le min sur des
// vecteurs en parallele) Ne pas regarder plus comment ca marche.
struct ReduceMin
{
private:
const Kokkos::View<const double*> x_;
public:
typedef Kokkos::View<const double*>::non_const_value_type value_type;
ReduceMin(const Kokkos::View<const double*>& x) : x_ (x) {}
typedef Kokkos::View<const double*>::size_type size_type;
KOKKOS_INLINE_FUNCTION void
operator() (const size_type i, value_type& update) const
{
if (x_(i) < update) {
update = x_(i);
}
}
KOKKOS_INLINE_FUNCTION void
join (volatile value_type& dst,
const volatile value_type& src) const
{
if (src < dst) {
dst = src;
}
}
KOKKOS_INLINE_FUNCTION void
init (value_type& dst) const
{ // The identity under max is -Inf.
dst= Kokkos::reduction_identity<value_type>::min();
}
};
// KOKKOS_INLINE_FUNCTION // Fonction qui calcule (rho c)_j
//const Kokkos::View<const double*>
//computeRhoCj(const Kokkos::View<const double*>& rhoj,
// const Kokkos::View<const double*>& cj)
//{
// Kokkos::parallel_for(m_mesh.numberOfCells(), KOKKOS_LAMBDA(const int& j) {
// m_rhocj[j] = rhoj[j]*cj[j];
// });
// return m_rhocj;
//}
// KOKKOS_INLINE_FUNCTION // Fonction qui calcule A_jr
//const Kokkos::View<const Rdd**>
//computeAjr(const Kokkos::View<const double*>& rhocj,
// const Kokkos::View<const Rd**>& Cjr) {
//const Kokkos::View<const unsigned short*> cell_nb_nodes
// = m_connectivity.cellNbNodes();
//Kokkos::parallel_for(m_mesh.numberOfCells(), KOKKOS_LAMBDA(const int& j) {
// for (int r=0; r<cell_nb_nodes[j]; ++r) {
// m_Ajr(j,r) = tensorProduct(rhocj(j)*Cjr(j,r), Cjr(j,r));
// }
// });
//return m_Ajr;
//}
// KOKKOS_INLINE_FUNCTION // Fonction qui calcule A_r (la matrice locale au sommet r)
//const Kokkos::View<const Rdd*>
//computeAr(const Kokkos::View<const Rdd**>& Ajr) {
//const Kokkos::View<const unsigned int**> node_cells = m_connectivity.nodeCells();
//const Kokkos::View<const unsigned short**> node_cell_local_node = m_connectivity.nodeCellLocalNode();
//const Kokkos::View<const unsigned short*> node_nb_cells = m_connectivity.nodeNbCells();
//Kokkos::parallel_for(m_mesh.numberOfNodes(), KOKKOS_LAMBDA(const int& r) {
// Rdd sum = zero;
// for (int j=0; j<node_nb_cells(r); ++j) {
// const int J = node_cells(r,j);
// const int R = node_cell_local_node(r,j);
// sum += Ajr(J,R);
// }
// m_Ar(r) = sum;
// });
//return m_Ar;
//}
//KOKKOS_INLINE_FUNCTION // Fonction qui calcule la somme b_r (le second membre au sommet r)
//const Kokkos::View<const Rd*>
//computeBr(const Kokkos::View<const Rdd**>& Ajr,
// const Kokkos::View<const Rd**>& Cjr,
// const Kokkos::View<const Rd*>& uj,
// const Kokkos::View<const double*>& pj) {
//const Kokkos::View<const unsigned int**>& node_cells = m_connectivity.nodeCells();
//const Kokkos::View<const unsigned short**>& node_cell_local_node = m_connectivity.nodeCellLocalNode();
//const Kokkos::View<const unsigned short*>& node_nb_cells = m_connectivity.nodeNbCells();
//Kokkos::parallel_for(m_mesh.numberOfNodes(), KOKKOS_LAMBDA(const int& r) {
// Rd& br = m_br(r);
// br = zero;
// for (int j=0; j<node_nb_cells(r); ++j) {
// const int J = node_cells(r,j);
// const int R = node_cell_local_node(r,j);
// br += Ajr(J,R)*uj(J) + pj(J)*Cjr(J,R);
// }
// });
//return m_br;
//}
//Kokkos::View<Rd*> // calcule u_r (vitesse au sommet r, pour se deplacer)
//computeUr(const Kokkos::View<const Rdd*>& Ar,
// const Kokkos::View<const Rd*>& br) {
//inverse(Ar, m_inv_Ar);
//const Kokkos::View<const Rdd*> invAr = m_inv_Ar;
//Kokkos::parallel_for(m_mesh.numberOfNodes(), KOKKOS_LAMBDA(const int& r) {
// m_ur[r]=invAr(r)*br(r);
//});
//m_ur[0]=zero;
//m_ur[m_mesh.numberOfNodes()-1]=zero;
//return m_ur;
//}
Kokkos::View<Rd**> // Fonction qui calcule F_jr // A MODIFIER
computeFjr(const Kokkos::View<const Rdd**>& Ajr,
const Kokkos::View<const Rd*>& ur,
const Kokkos::View<const Rd**>& Cjr,
const Kokkos::View<const Rd*>& uj,
const Kokkos::View<const double*>& pj) {
const Kokkos::View<const unsigned int**>& cell_nodes = m_connectivity.cellNodes();
const Kokkos::View<const unsigned short*> cell_nb_nodes
= m_connectivity.cellNbNodes();
Kokkos::parallel_for(m_mesh.numberOfCells(), KOKKOS_LAMBDA(const int& j) {
for (int r=0; r<cell_nb_nodes[j]; ++r) {
m_Fjr(j,r) = ((kjr(j,r)*Cjr(j,r) + kjr(j,r)*Cjr(j,r))/2)*((ujr(j,r)*Cjr(j,r) + ujr(j,r-1)*Cjr(j,r-1))/h(r));
}
});
return m_Fjr;
}
Kokkos::View<Rd**> // Fonction qui calcule G_jr // A MODIFIER
computeGjr(const Kokkos::View<const Rdd**>& Ajr,
const Kokkos::View<const Rd*>& ur,
const Kokkos::View<const Rd**>& Cjr,
const Kokkos::View<const Rd*>& uj,
const Kokkos::View<const double*>& pj) {
const Kokkos::View<const unsigned int**>& cell_nodes = m_connectivity.cellNodes();
const Kokkos::View<const unsigned short*> cell_nb_nodes
= m_connectivity.cellNbNodes();
Kokkos::parallel_for(m_mesh.numberOfCells(), KOKKOS_LAMBDA(const int& j) {
for (int r=0; r<cell_nb_nodes[j]; ++r) {
m_Gjr(j,r) = ((ujr(j,r)*Cjr(j,r) + ujr(j,r-1)*Cjr(j,r))/2)*Fjr(j,r);
}
});
return m_Gjr;
}
// Calcul la liste des inverses d'une liste de matrices (pour
// l'instant seulement $R^{1\times 1}$)
//void inverse(const Kokkos::View<const Rdd*>& A,
// Kokkos::View<Rdd*>& inv_A) const {
//Kokkos::parallel_for(A.size(), KOKKOS_LAMBDA(const int& r) {
// inv_A(r) = Rdd{1./(A(r)(0,0))};
// });
//}
// Calcul la liste des inverses d'une liste de reels
// void inverse(const Kokkos::View<const double*>& x,
// Kokkos::View<double*>& inv_x) const {
//Kokkos::parallel_for(x.size(), KOKKOS_LAMBDA(const int& r) {
// inv_x(r) = 1./x(r);
// });
// }
// Enchaine les operations pour calculer les flux (Fjr et ur) pour // A MODIFIER
// pouvoir derouler le schema
KOKKOS_INLINE_FUNCTION
void computeExplicitFluxes(const Kokkos::View<const Rd*>& xr,
const Kokkos::View<const Rd*>& xj,
const Kokkos::View<const double*>& rhoj,
const Kokkos::View<const Rd*>& uj,
const Kokkos::View<const double*>& pj,
const Kokkos::View<const double*>& cj,
const Kokkos::View<const double*>& Vj,
const Kokkos::View<const Rd**>& Cjr) {
const Kokkos::View<const double*> rhocj = computeRhoCj(rhoj, cj);
const Kokkos::View<const Rdd**> Ajr = computeAjr(rhocj, Cjr);
const Kokkos::View<const Rdd*> Ar = computeAr(Ajr);
const Kokkos::View<const Rd*> br = computeBr(Ajr, Cjr, uj, pj);
Kokkos::View<Rd*> ur = m_ur;
Kokkos::View<Rd**> Fjr = m_Fjr;
ur = computeUr(Ar, br);
Fjr = computeFjr(Ajr, ur, Cjr, uj, pj);
}
Kokkos::View<Rd*> m_br;
Kokkos::View<Rdd**> m_Ajr;
Kokkos::View<Rdd*> m_Ar;
Kokkos::View<Rdd*> m_inv_Ar;
Kokkos::View<Rd**> m_Fjr;
Kokkos::View<Rd*> m_ur;
Kokkos::View<double*> m_rhocj;
Kokkos::View<double*> m_Vj_over_cj;
public:
AcousticSolver(MeshData& mesh_data,
UnknownsType& unknowns)
: m_mesh_data(mesh_data),
m_mesh(mesh_data.mesh()),
m_connectivity(m_mesh.connectivity()),
m_br("br", m_mesh.numberOfNodes()),
m_Ajr("Ajr", m_mesh.numberOfCells(), m_connectivity.maxNbNodePerCell()),
m_Ar("Ar", m_mesh.numberOfNodes()),
m_inv_Ar("inv_Ar", m_mesh.numberOfNodes()),
m_Fjr("Fjr", m_mesh.numberOfCells(), m_connectivity.maxNbNodePerCell()),
m_ur("ur", m_mesh.numberOfNodes()),
m_rhocj("rho_c", m_mesh.numberOfCells()),
m_Vj_over_cj("Vj_over_cj", m_mesh.numberOfCells())
{
;
}
// Calcule une evaluation du pas de temps verifiant une CFL du type
// c*dt/dx<1. Utilise la reduction definie dans la structure // A MODIFIER
// ReduceMin. Ici, dx_j=V_j
KOKKOS_INLINE_FUNCTION
double acoustic_dt(const Kokkos::View<const double*>& Vj,
const Kokkos::View<const double*>& cj) const {
Kokkos::parallel_for(m_mesh.numberOfCells(), KOKKOS_LAMBDA(const int& j){
m_Vj_over_cj[j] = Vj[j]/cj[j];
});
double dt = std::numeric_limits<double>::max();
Kokkos::parallel_reduce(m_mesh.numberOfCells(), ReduceMin(m_Vj_over_cj), dt);
return dt;
}
// Avance la valeur des inconnues pendant un pas de temps dt // A MODIFIER
void computeNextStep(const double& t, const double& dt,
UnknownsType& unknowns)
{
Kokkos::View<double*> rhoj = unknowns.rhoj();
Kokkos::View<Rd*> uj = unknowns.uj();
Kokkos::View<double*> Ej = unknowns.Ej();
Kokkos::View<double*> ej = unknowns.ej();
Kokkos::View<double*> pj = unknowns.pj();
Kokkos::View<double*> gammaj = unknowns.gammaj();
Kokkos::View<double*> cj = unknowns.cj();
const Kokkos::View<const Rd*> xj = m_mesh_data.xj();
const Kokkos::View<const double*> Vj = m_mesh_data.Vj();
const Kokkos::View<const Rd**> Cjr = m_mesh_data.Cjr();
Kokkos::View<Rd*> xr = m_mesh.xr();
// Calcule les flux
computeExplicitFluxes(xr, xj, rhoj, uj, pj, cj, Vj, Cjr);
const Kokkos::View<const Rd**> Fjr = m_Fjr;
const Kokkos::View<const Rd*> ur = m_ur;
const Kokkos::View<const unsigned short*> cell_nb_nodes
= m_connectivity.cellNbNodes();
const Kokkos::View<const unsigned int**>& cell_nodes
= m_connectivity.cellNodes();
// Mise a jour de la vitesse et de l'energie totale specifique
const Kokkos::View<const double*> inv_mj = unknowns.invMj();
Kokkos::parallel_for(m_mesh.numberOfCells(), KOKKOS_LAMBDA(const int& j) {
Rd momentum_fluxes = zero;
double energy_fluxes = 0;
for (int R=0; R<cell_nb_nodes[j]; ++R) {
const int r=cell_nodes(j,R);
momentum_fluxes += Fjr(j,R);
energy_fluxes += (Fjr(j,R), ur[r]);
}
uj[j] -= (dt*inv_mj[j]) * momentum_fluxes;
Ej[j] -= (dt*inv_mj[j]) * energy_fluxes;
});
// Calcul de e par la formule e = E-0.5 u^2
Kokkos::parallel_for(m_mesh.numberOfCells(), KOKKOS_LAMBDA(const int& j) {
ej[j] = Ej[j] - 0.5 * (uj[j],uj[j]);
});
// deplace le maillage (ses sommets) en utilisant la vitesse
// donnee par le schema
Kokkos::parallel_for(m_mesh.numberOfNodes(), KOKKOS_LAMBDA(const int& r){
xr[r] += dt*ur[r];
});
// met a jour les quantites (geometriques) associees au maillage
m_mesh_data.updateAllData();
// Calcul de rho avec la formule Mj = Vj rhoj
const Kokkos::View<const double*> mj = unknowns.mj();
Kokkos::parallel_for(m_mesh.numberOfCells(), KOKKOS_LAMBDA(const int& j){
rhoj[j] = mj[j]/Vj[j];
});
}
};
#endif // FINITE_VOLUMES_DIFFUSION_HPP
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