Model order reduction of parameter-dependent particle laden flows

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388998%3A_____%2F24%3A00584514" target="_blank" >RIV/61388998:_____/24:00584514 - isvavai.cz</a>
Result on the web
<a href="http://www2.it.cas.cz/fm/im/im/proceeding/2024/15" target="_blank" >http://www2.it.cas.cz/fm/im/im/proceeding/2024/15</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/TPFM.2024.015" target="_blank" >10.14311/TPFM.2024.015</a>

Result language
angličtina
Original language name
Model order reduction of parameter-dependent particle laden flows
Original language description
In this contribution, we extend our previously-developed framework for model order reduction of transport-dominated systems towards parameterized cases. The method combines thenshifted proper orthogonal decomposition with interpolation via artificial neural networks. The resulting framework is an a-posteriori one, i.e., for parameterized systems, time-dependentnsolutions for several parameter values are required for the construction of the reduced-order model (ROM). The ROM can then be cheaply evaluated to predict the solution for previouslynunseen parameter values. The method is suitable for industry-relevant transport-dominated systems, such as particle-laden flows, where traditional mode-based methods, such as propernorthogonal decomposition (POD), often fail.
Czech name
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Czech description
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Project
<a href="/en/project/TM04000048" target="_blank" >TM04000048: Laser Improved Novel Surface Engineering and Repair of Tools</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

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

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