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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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MD5: 9C08A6C495D19A94ED7A83CE3177DD7D
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https://www.sciencedirect.com/science/article/pii/S0045782524006340
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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
UDC:
620.1/.2
ISSN on article:
1879-2138
DOI:
10.1016/j.cma.2024.117379
COBISS.SI-ID:
208896515
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
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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