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Soft Computing Techniques to Analyze the Turbulent Wake of a Wall-Mounted Square Cylinder
Univ Politecn Madrid, Sch Aerosp Engn, E-28040 Madrid, Spain..
Univ Politecn Madrid, Sch Aerosp Engn, E-28040 Madrid, Spain..
KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.ORCID iD: 0000-0001-9627-5903
KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW.ORCID iD: 0000-0001-6570-5499
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2020 (English)In: 14th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2019 / [ed] Alvarez, FM Lora, AT Munoz, JAS Quintian, H Corchado, E, Springer, 2020, Vol. 950, p. 577-586Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces several methods, generally used in fluid dynamics, to provide low-rank approximations. The algorithm describing these methods are mainly based on singular value decomposition (SVD) and dynamic mode decomposition (DMD) techniques, and are suitable to analyze turbulent flows. The application of these methods will be illustrated in the analysis of the turbulent wake of a wall-mounted cylinder, a geometry modeling a skyscraper. A brief discussion about the large and small size structures of the flow will provide the key ideas to represent the general dynamics of the flow using low-rank approximations. If the flow physics is understood, then it is possible to adapt these techniques, or some other strategies, to solve general complex problems with reduced computational cost. The main goal is to introduce these methods as machine learning strategies that could be potentially used in the field of fluid dynamics, and that can be extended to any other research field.

Place, publisher, year, edition, pages
Springer, 2020. Vol. 950, p. 577-586
Series
Advances in Intelligent Systems and Computing, ISSN 2194-5357 ; 950
Keywords [en]
Soft computing, Fluid dynamics, Turbulence flow, CFD, Data science, POD, DMD
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-263684DOI: 10.1007/978-3-030-20055-8_55ISI: 000490706700055Scopus ID: 2-s2.0-85065927402OAI: oai:DiVA.org:kth-263684DiVA, id: diva2:1368685
Conference
14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO), MAY 13-15, 2019, Seville, Spain
Note

QC 20191108

Available from: 2019-11-08 Created: 2019-11-08 Last updated: 2023-03-21Bibliographically approved

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Schlatter, PhilippVinuesa, Ricardo

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