#*------------------------------------------------------------------------------*
#* JAX-FLUIDS - *
#* *
#* A fully-differentiable CFD solver for compressible two-phase flows. *
#* Copyright (C) 2022 Deniz A. Bezgin, Aaron B. Buhendwa, Nikolaus A. Adams *
#* *
#* This program is free software: you can redistribute it and/or modify *
#* it under the terms of the GNU General Public License as published by *
#* the Free Software Foundation, either version 3 of the License, or *
#* (at your option) any later version. *
#* *
#* This program is distributed in the hope that it will be useful, *
#* but WITHOUT ANY WARRANTY; without even the implied warranty of *
#* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the *
#* GNU General Public License for more details. *
#* *
#* You should have received a copy of the GNU General Public License *
#* along with this program. If not, see <https://www.gnu.org/licenses/>. *
#* *
#*------------------------------------------------------------------------------*
#* *
#* CONTACT *
#* *
#* deniz.bezgin@tum.de // aaron.buhendwa@tum.de // nikolaus.adams@tum.de *
#* *
#*------------------------------------------------------------------------------*
#* *
#* Munich, April 15th, 2022 *
#* *
#*------------------------------------------------------------------------------*
from typing import Callable
import jax
import jax.numpy as jnp
from jaxfluids.materials.material_manager import MaterialManager
from jaxfluids.solvers.riemann_solvers.riemann_solver import RiemannSolver
from jaxfluids.utilities import get_fluxes_xi
[docs]
class HLL(RiemannSolver):
"""HLL Riemann Solver by Harten, Lax and van Leer
Harten et al. 1983
"""
def __init__(self, material_manager: MaterialManager, signal_speed: Callable) -> None:
super().__init__(material_manager, signal_speed)
[docs]
def solve_riemann_problem_xi(self, primes_L: jnp.ndarray, primes_R: jnp.ndarray,
cons_L: jnp.ndarray, cons_R: jnp.ndarray, axis: int, **kwargs) -> jnp.ndarray:
fluxes_left = get_fluxes_xi(primes_L, cons_L, axis)
fluxes_right = get_fluxes_xi(primes_R, cons_R, axis)
speed_of_sound_left = self.material_manager.get_speed_of_sound(p = primes_L[4], rho = primes_L[0])
speed_of_sound_right = self.material_manager.get_speed_of_sound(p = primes_R[4], rho = primes_R[0])
wave_speed_simple_L, wave_speed_simple_R = self.signal_speed(primes_L[axis+1], primes_R[axis+1], speed_of_sound_left, speed_of_sound_right,
rho_L = primes_L[0], rho_R = primes_R[0], p_L = primes_L[4], p_R = primes_R[4], gamma = self.material_manager.gamma)
wave_speed_left = jnp.minimum( wave_speed_simple_L, 0.0 )
wave_speed_right = jnp.maximum( wave_speed_simple_R, 0.0 )
fluxes_xi = (wave_speed_right * fluxes_left - wave_speed_left * fluxes_right +
wave_speed_left * wave_speed_right * ( cons_R - cons_L ) ) / ( wave_speed_right - wave_speed_left + self.eps)
return fluxes_xi