Application and Validation of a High Order Neural Networks Based Riemann Solver for 1D Euler Equations

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F24%3A00376023" target="_blank" >RIV/68407700:21220/24:00376023 - isvavai.cz</a>
Result on the web
<a href="https://am2024.uniza.sk/scientific-program/" target="_blank" >https://am2024.uniza.sk/scientific-program/</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Application and Validation of a High Order Neural Networks Based Riemann Solver for 1D Euler Equations
Original language description
The Riemann solver holds a key position in most computational fluid dynamics (CFD) codes, crucial for simulating compressible flows. The time to obtain the exact solution of the Riemann problem for ideal fluids is high because of the complexity of the model. Consequently, approximate Riemann solvers are preferred over exact ones to mitigate this complexity. This contribution describes application and validation of state-of-the-art Riemann solver, which very accurately approximates the behaviour of an exact Riemann solver needing only a fraction of the exact solver’s computational time. This is achieved by employing a specific type of neural networks. This new approximate Riemann solver is implemented in classical Godunov’s scheme and validated on the well-known Sod’s shock tube problem with promising results in terms of accuracy and time efficiency.
Czech name
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Czech description
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Project
<a href="/en/project/EF16_019%2F0000826" target="_blank" >EF16_019/0000826: Center of Advanced Aerospace Technology</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
25th International Scientific Conference APPLIED MECHANICS 2024 AM 2024 BOOK OF ARTICLES
ISBN
978-80-554-2090-5
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
166-169
Publisher name
University of Žilina
Place of publication
Žilina
Event location
Vysoké Tatry
Event date
Apr 17, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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