A Monte-Carlo ab-initio algorithm for the multiscale simulation of compressible multiphase flows
Abstract
We propose a novel Monte-Carlo based ab-initio algorithm for directly computing the statistics for quantities of interest in an immiscible two-phase compressible flow. Our algorithm samples the underlying probability space and evolves these samples with a sharp interface front-tracking scheme. Consequently, statistical information is generated without resorting to any closure assumptions and information about the underlying microstructure is implicitly included. The proposed algorithm is tested on a suite of numerical experiments and we observe that the ab-initio procedure can simulate a variety of flow regimes robustly and converges with respect of refinement of number of samples as well as number of bubbles per volume. The results are also compared with a state-of-the-art discrete equation method to reveal the inherent limitations of existing macroscopic models.
Cite
@article{arxiv.2303.16540,
title = {A Monte-Carlo ab-initio algorithm for the multiscale simulation of compressible multiphase flows},
author = {Marco Petrella and Remi Abgrall and Siddhartha Mishra},
journal= {arXiv preprint arXiv:2303.16540},
year = {2023}
}