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Bibliographic Details
Main Authors: Storcks, Leonard, Buck, Tobias
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.23093
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author Storcks, Leonard
Buck, Tobias
author_facet Storcks, Leonard
Buck, Tobias
contents We present jf1uids, a one-dimensional fluid solver that can, by virtue of a geometric formulation of the Euler equations, model radially symmetric fluid problems in a conservative manner, i.e., without losing mass or energy. For spherical problems, such as ideal supernova explosions or stellar wind-blown bubble expansions, simulating only along a radial dimension drastically reduces compute and memory demands compared to a full three-dimensional method. This simplification also alleviates constraints on backpropagation through the solver. Written in JAX, jf1uids is a GPU-compatible and fully differentiable simulator. We demonstrate the advantages of this differentiable physics simulator by retrieving the wind's parameters for an adiabatic stellar wind expansion from the final fluid state using gradient descent. As part of a larger "stellar winds, cosmic rays and machine learning" research track, jf1uids serves as a solid foundation to be extended with additional physics modules, foremost cosmic rays and a neural-net powered gas-cooling surrogate and improved by higher order and more accurate numerical schemes. All code is available under https://github.com/leo1200/jf1uids/.
format Preprint
id arxiv_https___arxiv_org_abs_2410_23093
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Differentiable Conservative Radially Symmetric Fluid Simulations and Stellar Winds -- jf1uids
Storcks, Leonard
Buck, Tobias
Fluid Dynamics
We present jf1uids, a one-dimensional fluid solver that can, by virtue of a geometric formulation of the Euler equations, model radially symmetric fluid problems in a conservative manner, i.e., without losing mass or energy. For spherical problems, such as ideal supernova explosions or stellar wind-blown bubble expansions, simulating only along a radial dimension drastically reduces compute and memory demands compared to a full three-dimensional method. This simplification also alleviates constraints on backpropagation through the solver. Written in JAX, jf1uids is a GPU-compatible and fully differentiable simulator. We demonstrate the advantages of this differentiable physics simulator by retrieving the wind's parameters for an adiabatic stellar wind expansion from the final fluid state using gradient descent. As part of a larger "stellar winds, cosmic rays and machine learning" research track, jf1uids serves as a solid foundation to be extended with additional physics modules, foremost cosmic rays and a neural-net powered gas-cooling surrogate and improved by higher order and more accurate numerical schemes. All code is available under https://github.com/leo1200/jf1uids/.
title Differentiable Conservative Radially Symmetric Fluid Simulations and Stellar Winds -- jf1uids
topic Fluid Dynamics
url https://arxiv.org/abs/2410.23093