Koopman-inspired data-driven quantification of fluid–structure energy transfers

Author:

Li Cruz Y.ORCID,Zhang LikaiORCID,Li SijiaORCID,Zhang XuelinORCID,Chen ZengshunORCID,Fu YunfeiORCID,Lin XishengORCID,Peng Daniel ZiyueORCID,Wang YixiangORCID,Zhang BingchaoORCID,Zhou LeiORCID,Wang YunlongORCID,Liu Haiqing,Weerasuriya Asiri U.1ORCID,Tse K. T.ORCID,Yang QingshanORCID

Affiliation:

1. Department of Construction and Quality Management, School of Science and Technology, Hong Kong Metropolitan University 6 , Ho Man Tin, Hong Kong, China

Abstract

The linear-time-invariance notion to the Koopman analysis is a recent advance in fluid mechanics [Li et al., “The linear-time-invariance notion to the Koopman analysis: The architecture, pedagogical rendering, and fluid–structure association,” Phys. Fluids 34(12), 125136 (2022c) and Li et al., “The linear-time-invariance notion of the Koopman analysis—Part 2. Dynamic Koopman modes, physics interpretations and phenomenological analysis of the prism wake,” J. Fluid Mech. 959, A15 (2023a)], targeting the long-standing issue of correlating nonlinear excitation and response phenomena in fluid–structure interactions (FSI), or, in the simplified case, flow over rigid obstacles. Continuing the serial research, this work presents a data-driven, Koopman-inspired methodology to decouple nonlinear FSI by establishing cause-and-effect correspondences between structure surface pressure and the flow field. Exploiting unique features of the Koopman operator, the new methodology renders dynamic visualizations of in-sync, fluid–structure-coupled Koopman modes possible, fostering phenomenological analysis and statistical quantifications of FSI energy transfers. Instantaneous contribution contours and densities offer new angles to evaluate pathways of energy amplification and diminution. The methodology enables better descriptions and interpretations of phenomena occurring in the flow and on the boundary (walls) of an FSI domain and readily applies to a broad spectrum of engineering problems given its data-driven nature.

Funder

National Natural Science Foundation of China

Supporting Scheme of Chongqing for Returned Overseas Chinese Entrepreneurial Start-ups

Fundamental Research Funds for the Central Universities

The Start-Up Found of Chongqing University

Research Grants Council, University Grants Committee

Natural Science Foundation of Chongqing Municipality

The Key Project of Technological Innovation and Application Development in Chongqing

The Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory

The Young Researcher Fund of Sun Yat-sen University

Research Grants Council of Hong Kong Special Administrative Region, China

Publisher

AIP Publishing

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