File Kurganov.h

#include "General.h"
#include "Param.h"
#include "Arrays.h"
#include "Forcing.h"
#include "MemManagement.h"
#include "Util_CPU.h"
#include "Spherical.h"

Public Functions

Type	Name
__host__ void	AddSlopeSourceXCPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * zb) Host function for adding topographic slope source terms in X direction.
__global__ void	AddSlopeSourceXGPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * zb) CUDA kernel for adding topographic slope source terms in X direction.
__host__ void	AddSlopeSourceYCPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * zb) Host function for adding topographic slope source terms in Y direction.
__global__ void	AddSlopeSourceYGPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * zb) CUDA kernel for adding topographic slope source terms in Y direction.
__host__ __device__ T	KurgSolver (T g, T delta, T epsi, T CFL, T cm, T fm, T hp, T hm, T up, T um, T & fh, T & fu) Kurganov-Petrova approximate Riemann solver for fluxes and time step.
__host__ void	updateKurgXATMCPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * dtmax, T * zb, T * Patm, T * dPdx) Host function for updating X-direction fluxes with atmospheric pressure effects.
__global__ void	updateKurgXATMGPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * dtmax, T * zb, T * Patm, T * dPdx) CUDA kernel for updating X-direction fluxes with atmospheric pressure effects.
__host__ void	updateKurgXCPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * dtmax, T * zb) Host function for updating X-direction fluxes using the Kurganov scheme.
__global__ void	updateKurgXGPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * dtmax, T * zb) CUDA kernel for updating X-direction fluxes using the Kurganov scheme.
__host__ void	updateKurgYATMCPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * dtmax, T * zb, T * Patm, T * dPdy) Host function for updating Y-direction fluxes with atmospheric pressure effects.
__global__ void	updateKurgYATMGPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * dtmax, T * zb, T * Patm, T * dPdy) CUDA kernel for updating Y-direction fluxes with atmospheric pressure effects.
__host__ void	updateKurgYCPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * dtmax, T * zb) Host function for updating Y-direction fluxes using the Kurganov scheme.
__global__ void	updateKurgYGPU (Param XParam, BlockP< T > XBlock, EvolvingP< T > XEv, GradientsP< T > XGrad, FluxP< T > XFlux, T * dtmax, T * zb) CUDA kernel for updating Y-direction fluxes using the Kurganov scheme.

Public Functions Documentation

function AddSlopeSourceXCPU

Host function for adding topographic slope source terms in X direction.

template<class T>
__host__ void AddSlopeSourceXCPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * zb
)

Updates fluxes with slope source terms for well-balanced solutions on CPU (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
zb Bathymetry array

function AddSlopeSourceXGPU

CUDA kernel for adding topographic slope source terms in X direction.

template<class T>
__global__ void AddSlopeSourceXGPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * zb
)

Updates fluxes with slope source terms for well-balanced solutions (based on Kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
zb Bathymetry array

function AddSlopeSourceYCPU

Host function for adding topographic slope source terms in Y direction.

template<class T>
__host__ void AddSlopeSourceYCPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * zb
)

Updates fluxes with slope source terms for well-balanced solutions in Y direction on CPU (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
zb Bathymetry array

function AddSlopeSourceYGPU

CUDA kernel for adding topographic slope source terms in Y direction.

template<class T>
__global__ void AddSlopeSourceYGPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * zb
)

Updates fluxes with slope source terms for well-balanced solutions in Y direction (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
zb Bathymetry array

function KurgSolver

Kurganov-Petrova approximate Riemann solver for fluxes and time step.

template<class T>
__host__ __device__ T KurgSolver (
    T g,
    T delta,
    T epsi,
    T CFL,
    T cm,
    T fm,
    T hp,
    T hm,
    T up,
    T um,
    T & fh,
    T & fu
)

Computes fluxes and time step for the Kurganov scheme given left/right states and velocities (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

g Gravity
delta Cell size
epsi Small epsilon for stability
CFL CFL number
cm Metric coefficient
fm Flux metric
hp Water depth (plus side)
hm Water depth (minus side)
up Velocity (plus side)
um Velocity (minus side)
fh Output: flux for h
fu Output: flux for u

Returns:

Time step

function updateKurgXATMCPU

Host function for updating X-direction fluxes with atmospheric pressure effects.

template<class T>
__host__ void updateKurgXATMCPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * dtmax,
    T * zb,
    T * Patm,
    T * dPdx
)

Computes fluxes and time step constraints for each cell in the X direction on CPU, including atmospheric pressure terms (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
dtmax Maximum time step array
zb Bathymetry array
Patm Atmospheric pressure array
dPdx Pressure gradient array

function updateKurgXATMGPU

CUDA kernel for updating X-direction fluxes with atmospheric pressure effects.

template<class T>
__global__ void updateKurgXATMGPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * dtmax,
    T * zb,
    T * Patm,
    T * dPdx
)

Computes fluxes and time step constraints for each cell in the X direction, including atmospheric pressure terms (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
dtmax Maximum time step array
zb Bathymetry array
Patm Atmospheric pressure array
dPdx Pressure gradient array

function updateKurgXCPU

Host function for updating X-direction fluxes using the Kurganov scheme.

template<class T>
__host__ void updateKurgXCPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * dtmax,
    T * zb
)

Computes fluxes and time step constraints for each cell in the X direction on CPU (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
dtmax Maximum time step array
zb Bathymetry array

function updateKurgXGPU

CUDA kernel for updating X-direction fluxes using the Kurganov scheme.

template<class T>
__global__ void updateKurgXGPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * dtmax,
    T * zb
)

Computes fluxes and time step constraints for each cell in the X direction (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
dtmax Maximum time step array
zb Bathymetry array

function updateKurgYATMCPU

Host function for updating Y-direction fluxes with atmospheric pressure effects.

template<class T>
__host__ void updateKurgYATMCPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * dtmax,
    T * zb,
    T * Patm,
    T * dPdy
)

Computes fluxes and time step constraints for each cell in the Y direction on CPU, including atmospheric pressure terms (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
dtmax Maximum time step array
zb Bathymetry array
Patm Atmospheric pressure array
dPdy Pressure gradient array

function updateKurgYATMGPU

CUDA kernel for updating Y-direction fluxes with atmospheric pressure effects.

template<class T>
__global__ void updateKurgYATMGPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * dtmax,
    T * zb,
    T * Patm,
    T * dPdy
)

Computes fluxes and time step constraints for each cell in the Y direction, including atmospheric pressure terms (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
dtmax Maximum time step array
zb Bathymetry array
Patm Atmospheric pressure array
dPdy Pressure gradient array

function updateKurgYCPU

Host function for updating Y-direction fluxes using the Kurganov scheme.

template<class T>
__host__ void updateKurgYCPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * dtmax,
    T * zb
)

Computes fluxes and time step constraints for each cell in the Y direction on CPU (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
dtmax Maximum time step array
zb Bathymetry array

function updateKurgYGPU

CUDA kernel for updating Y-direction fluxes using the Kurganov scheme.

template<class T>
__global__ void updateKurgYGPU (
    Param XParam,
    BlockP < T > XBlock,
    EvolvingP < T > XEv,
    GradientsP < T > XGrad,
    FluxP < T > XFlux,
    T * dtmax,
    T * zb
)

Computes fluxes and time step constraints for each cell in the Y direction (based on kurganov and Petrova 2007).

Template parameters:

T Data type

Parameters:

XParam Simulation parameters
XBlock Block parameters
XEv Evolving variables
XGrad Gradients
XFlux Fluxes
dtmax Maximum time step array
zb Bathymetry array

The documentation for this class was generated from the following file src/Kurganov.h