FiniteVolumesDiffusion.hpp

#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; // 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)
  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::View<Rd**>  // Fonction qui calcule F_jr 
  computeFjr(const Kokkos::View<const Rd**>& Cjr,
	     const Kokkos::View<const Rd*>& uj,
	     const Kokkos::View<const Rd*>& xr,
	     const Kokkos::View<const double*>& kj) {
    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) = ((kj(cell_nodes(j,r)) + kj(cell_nodes(j,r)-1))/(2*(xj(cell_nodes(j,r))-xj(cell_nodes(j,r)-1))))*uj(j,r)*Cjr(j,r); 
	}
      });

    return m_Fjr;
  }

  Kokkos::View<Rd**>  // Fonction qui calcule G_jr 
  computeGjr(const Kokkos::View<const Rd*>& uj,
	     const Kokkos::View<const double*>& Fjr) {
    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) = ((uj(cell_nodes(j,r)) + uj(cell_nodes(j,r)-1))/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 Gjr) pour
  // 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*>& kj,
			     const Kokkos::View<const double*>& rhoj,
			     const Kokkos::View<const Rd*>& uj,
			     const Kokkos::View<const Rd**>& Cjr) {
    Kokkos::View<Rd**> Fjr = m_Fjr; 
    Fjr = computeFjr(Cjr, uj, xr, kj);
    Kokkos::View<Rd**> Gjr = m_Gjr; 
    Gjr = computeGjr(uj, Fjr);
  }

  Kokkos::View<Rd**> m_Fjr;
  Kokkos::View<double*> m_CFL;

public:
  FiniteVolumesDiffusion(MeshData& mesh_data,
		 UnknownsType& unknowns)
    : m_mesh_data(mesh_data),
      m_mesh(mesh_data.mesh()),
      m_connectivity(m_mesh.connectivity()),
      m_Fjr("Fjr", m_mesh.numberOfCells(), m_connectivity.maxNbNodePerCell()),
      m_CFL("CFL", m_mesh.numberOfCells())
  {
    ;
  }

  // Calcule une evaluation du pas de temps verifiant le CFL parabolique
  // Utilise la reduction definie dans la structure ReduceMin. Ici, dx_j=V_j
  KOKKOS_INLINE_FUNCTION
  double diffusion_dt(const Kokkos::View<const double*>& Vj,
		      const Kokkos::View<const double*>& rhoj,
		      const Kokkos::View<const Rd*>& xr,
		      const Kokkos::View<const Rd*>& kj) const {
    Kokkos::View<double*> dt_j("dt_j", m_mesh.numberOfCells());

    Kokkos::parallel_for(m_mesh.numberOfCells(), KOKKOS_LAMBDA(const int& j){
	m_CFL(j) = rhoj(j)*Vj(j)*min(xj(j+1)-xj(j), xj(j)-xj(j-1))*(2./(kj(j+1) + 2*kj(j) + kj(j-1)));
      });

    double dt = std::numeric_limits<double>::max();
    Kokkos::parallel_reduce(m_mesh.numberOfCells(), ReduceMin(dt_j), 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*> gammaj = unknowns.gammaj();

    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, Cjr);

    const Kokkos::View<const Rd**> Fjr = m_Fjr;
    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   += Gjr(j,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]);
      });

    // 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