Schema_Backward_Differentiation_order_3.cpp

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#include <Schema_Backward_Differentiation_order_3.h>
 
#include <Equation_base.h>
#include <Probleme_base.h>
#include <Probleme_Couple.h>
#include <Milieu_base.h>
#include <Param.h>
 
#include <communications.h>
#include <Matrice_Morse.h>
 
Implemente_instanciable(Schema_Backward_Differentiation_order_3,"Schema_Backward_Differentiation_order_3",Schema_Backward_Differentiation_base);
// XD schema_backward_differentiation_order_3 schema_implicite_base schema_backward_differentiation_order_3 INHERITS_BRACE not_set
// XD attr facsec_max floattant facsec_max OPT Maximum ratio allowed between time step and stability time returned by
// XD_CONT CFL condition. The initial ratio given by facsec keyword is changed during the calculation with the implicit
// XD_CONT scheme but it couldn\'t be higher than facsec_max value.NL2 Warning: Some implicit schemes do not permit high
// XD_CONT facsec_max, example Schema_Adams_Moulton_order_3 needs facsec=facsec_max=1. NL2 Advice:NL2 The calculation
// XD_CONT may start with a facsec specified by the user and increased by the algorithm up to the facsec_max limit. But
// XD_CONT the user can also choose to specify a constant facsec (facsec_max will be set to facsec value then). Faster
// XD_CONT convergence has been seen and depends on the kind of calculation: NL2-Hydraulic only or thermal hydraulic
// XD_CONT with forced convection and low coupling between velocity and temperature (Boussinesq value beta low), facsec
// XD_CONT between 20-30NL2-Thermal hydraulic with forced convection and strong coupling between velocity and
// XD_CONT temperature (Boussinesq value beta high), facsec between 90-100 NL2-Thermohydralic with natural convection,
// XD_CONT facsec around 300NL2 -Conduction only, facsec can be set to a very high value (1e8) as if the scheme was
// XD_CONT unconditionally stableNL2These values can also be used as rule of thumb for initial facsec with a facsec_max
// XD_CONT limit higher.
 
 
 
/*! @brief Simple call to Schema_Temps_base::printOn(Sortie&). Writes the time scheme to an output stream.
 *
 * @param (Sortie& s) an output stream
 * @return (Sortie&) the modified output stream
 */
Sortie& Schema_Backward_Differentiation_order_3::printOn(Sortie& s) const
{
  return  Schema_Backward_Differentiation_base::printOn(s);
}
 
 
/*! @brief Reads the time scheme from an input stream.
 *
 * Simple call to Schema_Temps_base::readOn(Entree&).
 *
 * @param (Entree& s) an input stream
 * @return (Entree&) the modified input stream
 */
Entree& Schema_Backward_Differentiation_order_3::readOn(Entree& s)
{
  return Schema_Backward_Differentiation_base::readOn(s);
}
 
////////////////////////////////
//                            //
// Scheme characteristics     //
//                            //
////////////////////////////////
 
 
/*! @brief Returns the number of time values to retain.
 *
 * Here: n-1, n and n+1, so 3.
 *
 */
int Schema_Backward_Differentiation_order_3::nb_valeurs_temporelles() const
{
  return 5 ;
}
 
int Schema_Backward_Differentiation_order_3::nb_valeurs_passees() const
{
  return 2;
}
 
int Schema_Backward_Differentiation_order_3::nb_pas_dt_seuil() const
{
  return 2;
}
 
/////////////////////////////////////////
//                                     //
// End of scheme characteristics       //
//                                     //
/////////////////////////////////////////
 
void Schema_Backward_Differentiation_order_3::compute_backward_differentiation_coefficients(double time_step, const DoubleTab& times) const
{
  assert(times.size_array() == 4); //past, present and future times, stored in ascending order inside "times" table
 
  if (backward_differentiation_coefficients_.size_array() != 4)
    {
      backward_differentiation_coefficients_.resize(4,RESIZE_OPTIONS::NOCOPY_NOINIT);
    }
 
  double alpha_1 = 1.;                            // for times[2] which means present time
  double alpha_2 = time_step/(times[3]-times[1]); // for times[1] which means past time that is to say t(n-1)
  double alpha_3 = time_step/(times[3]-times[0]); // for times[0] which means past past time that is to say t(n-2)
 
  backward_differentiation_coefficients_[3] = 1./(alpha_1+alpha_2+alpha_3);                                                                  //for times[3] which means future time
  backward_differentiation_coefficients_[2] = alpha_1*backward_differentiation_coefficients_[3]/((1.-alpha_2/alpha_1)*(1.-alpha_3/alpha_1)); //for times[2] which means past time
  backward_differentiation_coefficients_[1] = alpha_2*backward_differentiation_coefficients_[3]/((1.-alpha_1/alpha_2)*(1.-alpha_3/alpha_2)); //for times[1] which means past time
  backward_differentiation_coefficients_[0] = alpha_3*backward_differentiation_coefficients_[3]/((1.-alpha_1/alpha_3)*(1.-alpha_2/alpha_3)); //for times[0] which means past past time
}