%0 Generic %1 magiera.rohde:molecular:2022 %A Magiera, Jim %A Rohde, Christian %D 2022 %J arXiv e-prints %K ians imported myown vor:mathematik vorlaeufig %R 10.48550/arXiv.2204.02233 %T A Molecular--Continuum Multiscale Model for Inviscid Liquid--Vapor Flow with Sharp Interfaces %U https://doi.org/10.48550/arXiv.2204.02233 %X The dynamics of compressible liquid--vapor flow depends sensitively on the microscale behavior at the phase boundary. We consider a sharp-interface approach, and propose a multiscale model to describe liquid--vapor flow accurately, without imposing ad-hoc closure relations on the continuum scale. The multiscale model combines the Euler equations on the continuum scale with molecular-scale particle simulations that govern the interface motion. We rely on an interface-preserving moving mesh finite volume method to discretize the continuum-scale sharp-interface flow in a conservative manner. Computational efficiency, while preserving physical properties, is achieved by a surrogate solver for the interface dynamics based on constraint-aware neural networks. The multiscale model is presented in its general form, and applied to regimes of temperature-dependent liquid--vapor flow which have not been accessible before.

@preprint{magiera.rohde:molecular:2022, abstract = {The dynamics of compressible liquid--vapor flow depends sensitively on the microscale behavior at the phase boundary. We consider a sharp-interface approach, and propose a multiscale model to describe liquid--vapor flow accurately, without imposing ad-hoc closure relations on the continuum scale. The multiscale model combines the Euler equations on the continuum scale with molecular-scale particle simulations that govern the interface motion. We rely on an interface-preserving moving mesh finite volume method to discretize the continuum-scale sharp-interface flow in a conservative manner. Computational efficiency, while preserving physical properties, is achieved by a surrogate solver for the interface dynamics based on constraint-aware neural networks. The multiscale model is presented in its general form, and applied to regimes of temperature-dependent liquid--vapor flow which have not been accessible before.}, added-at = {2022-04-07T10:56:22.000+0200}, archiveprefix = {arXiv}, author = {Magiera, Jim and Rohde, Christian}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2db711192a8201d124b734c4db206feda/jimmagiera}, doi = {10.48550/arXiv.2204.02233}, eprint = {2204.02233}, eprintclass = {math.NA}, eprinttype = {arXiv}, file = {online:http\:/arxiv.org/pdf/2204.02233v1:PDF}, interhash = {2f984181c78ce8870ad424f548dfa564}, intrahash = {db711192a8201d124b734c4db206feda}, journal = {arXiv e-prints}, keywords = {ians imported myown vor:mathematik vorlaeufig}, langid = {english}, primaryclass = {math.NA}, timestamp = {2022-04-07T08:58:08.000+0200}, title = {A Molecular--Continuum Multiscale Model for Inviscid Liquid--Vapor Flow with Sharp Interfaces}, url = {https://doi.org/10.48550/arXiv.2204.02233}, year = 2022 }