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Learning macroscopic equations of motion from dissipative particle dynamics simulations of fluids
ID Jug, Matevž (Author), ID Svenšek, Daniel (Author), ID Potisk, Tilen (Author), ID Praprotnik, Matej (Author)

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Abstract
Macroscopic descriptions of both natural and engineered materials usually include a number of phenomenological parameters that have to be estimated from experiments or large-scale microscopic simulations. When dealing with advanced complex materials, these descriptions are sometimes not a priori available or not even known. Using sparsity-promoting techniques one can extract macroscopic dynamic models directly from particle-based simulations. In this work, we showcase such an approach on a simple fluid and test its robustness. We introduce a novel measure for automatic macroscopic model selection that combines stability and accuracy of a model. Using this measure and employing only a few physics-based assumptions, we are able to infer both the mass continuity equation and an equation for the conservation of linear momentum. Moreover, the extracted phenomenological and non-phenomenological parameters agree well with their numerically measured values and the well-known semi-empirical estimates. The presented model selection framework can be applied to simulations or experimental data of more complex systems, described in general by a rich set of coupled nonlinear macroscopic equations.

Language:English
Keywords:sparsity, model selection, particle simulations, macroscopic dynamics, regression
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FMF - Faculty of Mathematics and Physics
Publication status:Published
Publication version:Version of Record
Year:2024
Number of pages:15 str.
Numbering:Vol. 432, pt. A, art. 117379
PID:20.500.12556/RUL-162771 This link opens in a new window
UDC:620.1/.2
ISSN on article:1879-2138
DOI:10.1016/j.cma.2024.117379 This link opens in a new window
COBISS.SI-ID:208896515 This link opens in a new window
Publication date in RUL:27.09.2024
Views:98
Downloads:559
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Record is a part of a journal

Title:Computer methods in applied mechanics and engineering
Publisher:Elsevier
ISSN:1879-2138
COBISS.SI-ID:22956805 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:materiali, simulacije, dinamika, regresija

Projects

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P1-0002
Name:Večskalno modeliranje in simulacija mehke in biološke snovi v in izven ravnovesja

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J1-50035
Name:Odkrivanje makroskopskih modelov kompleksnih tekočin z uporabo poenostavitvenih metod

Funder:EC - European Commission
Funding programme:H2020
Project number:885155
Name:Multiscale modeling and simulation approaches for biomedical ultrasonic applications
Acronym:MULTraSonicA

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