kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Higher-order dynamic mode decomposition on-the-fly: A low-order algorithm for complex fluid flows
Technol Grad Univ, Okinawa Inst Sci, Complex Fluids & Flows Unit, 1919-1 Tancha, Onna, Okinawa 9040495, Japan..
KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW. KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Fluid Mechanics and Engineering Acoustics.ORCID iD: 0000-0001-9627-5903
KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW. KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Fluid Mechanics and Engineering Acoustics.ORCID iD: 0000-0001-6570-5499
Univ Politecn Madrid, ETSI Aeronaut & Espacio, Plaza Cardenal Cisneros 3, Madrid 28040, Spain..
2023 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 475, article id 111849Article in journal (Refereed) Published
Abstract [en]

This article presents a new method to identify the main patterns describing the flow motion in complex flows. The algorithm is an extension of the higher-order dynamic mode decomposition (HODMD), which compresses the snapshots from the analysed database and progressively updates new compressed snapshots on-the-fly, so it is denoted as HODMD on -the-fly (HODMD-of). This algorithm can be applied in parallel to the numerical simulations (or experiments), and it exhibits two main advantages over offline algorithms: (i) it automatically selects on-the-fly the number of necessary snapshots from the database to identify the relevant dynamics; and (ii) it can be used from the beginning of a numerical simulation (or experiment), since it uses a sliding-window to automatically select, also on-the-fly, the suitable interval to perform the data analysis, i.e. it automatically identifies and discards the transient dynamics. The HODMD-of algorithm is suitable to build reduced order models, which have a much lower computational cost than the original simulation. The performance of the method has been tested in three different cases: the axi-symmetric synthetic jet, the three-dimensional wake of a circular cylinder and the turbulent wake behind a wall-mounted square cylinder. The obtained speed-up factors are around 7 with respect to HODMD; this value depends on the simulation and the configuration of the hyperparameters. HODMD-of also provides a significant reduction of the memory requirements, between 40 - 80% amongst the two-and three-dimensional cases studied in this paper.

Place, publisher, year, edition, pages
Elsevier BV , 2023. Vol. 475, article id 111849
Keywords [en]
Data-driven methods, Machine learning, Higher-order dynamic mode decomposition, Turbulent flows, Synthetic jets, Three-dimensional cylinder
National Category
Computer Sciences Fluid Mechanics
Identifiers
URN: urn:nbn:se:kth:diva-323634DOI: 10.1016/j.jcp.2022.111849ISI: 000912635900001Scopus ID: 2-s2.0-85144304446OAI: oai:DiVA.org:kth-323634DiVA, id: diva2:1735128
Note

QC 20230208

Available from: 2023-02-08 Created: 2023-02-08 Last updated: 2025-02-09Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Schlatter, PhilippVinuesa, Ricardo

Search in DiVA

By author/editor
Schlatter, PhilippVinuesa, Ricardo
By organisation
Linné Flow Center, FLOWFluid Mechanics and Engineering Acoustics
In the same journal
Journal of Computational Physics
Computer SciencesFluid Mechanics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 306 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf