Shifted proper orthogonal decomposition and artificial neural networks for time-continuous reduced order models of transport-dominated systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388998%3A_____%2F22%3A00560836" target="_blank" >RIV/61388998:_____/22:00560836 - isvavai.cz</a>
Result on the web
<a href="http://www2.it.cas.cz/fm2015/im/admin/showfile/data/my/Papers/2022/16-TPFM2022.pdf" target="_blank" >http://www2.it.cas.cz/fm2015/im/admin/showfile/data/my/Papers/2022/16-TPFM2022.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/TPFM.2022.016" target="_blank" >10.14311/TPFM.2022.016</a>
Alternative languages
Result language
angličtina
Original language name
Shifted proper orthogonal decomposition and artificial neural networks for time-continuous reduced order models of transport-dominated systems
Original language description
Transport-dominated systems are pervasive in both industrial and scientific applications. However, they provide a challenge for common mode-based model order reduction (MOR) approaches, as they often require a large number of linear modes to obtain a sufficiently accurate reduced order model (ROM). In this work, we utilize the shifted proper orthogonal decomposition (sPOD), a methodology tailored for MOR of transport-dominated systems, and combine it with an interpolation based on artificial neural networks (ANN) to obtain a time-continuous ROM usable in engineering practice. The resulting MOR framework is purely data-driven, i.e., it does not require any information on the full order model (FOM) structure, which extends its applicability. On the other hand, compared to the standard projection-based approaches to MOR, the dimensionality reduction utilizing sPOD and ANN is significantly more computationally expensive since it requires a solution of high-dimensional optimization problems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20302 - Applied mechanics
Result continuities
Project
<a href="/en/project/EF15_003%2F0000493" target="_blank" >EF15_003/0000493: Centre of Excellence for Nonlinear Dynamic Behaviour of Advanced Materials in Engineering</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Topical Problems of Fluid Mechanics 2022
ISBN
978-80-87012-77-2
ISSN
2336-5781
e-ISSN
—
Number of pages
8
Pages from-to
111-118
Publisher name
Ústav termomechaniky AV ČR, v. v. i.
Place of publication
Praha
Event location
Praha
Event date
Feb 16, 2022
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
001235659500016