#*------------------------------------------------------------------------------*
#* 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 List
import jax.numpy as jnp
from jaxfluids.time_integration.time_integrator import TimeIntegrator
[docs]
class Euler(TimeIntegrator):
"""First-order explicit Euler time integration scheme
"""
def __init__(self, nh: int, inactive_axis: List) -> None:
super(Euler, self).__init__(nh, inactive_axis)
self.no_stages = 1
self.timestep_multiplier = (1.0,)
self.timestep_increment_factor = (1.0,)
[docs]
def integrate(self, cons: jnp.ndarray, rhs: jnp.ndarray, timestep: float, stage: int) -> jnp.ndarray:
cons = self.integrate_conservatives(cons, rhs, timestep)
return cons