Reduced Order Modelling for Wave-Structure Modelling

Fatma Güler Eroglu, N. T. Mücke, Jens Visbech, Allan Peter Engsig-Karup

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Abstract

In offshore engineering, the simulation of ocean waves and their interaction with structures has become more prominent. High-fidelity simulations of these problems are costly and burden the computational resources. To address this issue, we investigate proper orthogonal decomposition (POD) [1] based reduced-order modelling for wave structure interaction problems of relevance for offshore engineering. The POD method is based on generating a low-dimensional and much more efficient reduced order model representing the full order model based on a set of governing equations, e.g., describing fully nonlinear potential flow [2]. Therefore, significant time and cost savings can be achieved through using POD for the Laplace problem as demonstrated already for dispersive and nonlinear water wave modelling [3]. In this talk, we present our latest progress on developing reduced order models based on temporal discretizations using explicit Runge-Kutta methods and the spatial discretizations with the spectral element method (SEM) that supports unstructured meshes allowing for the handling of the wave propagation problem as well as the geometries of complex structures [4,5]. The results of several numerical tests used as benchmark problems are presented, illuminating that acceleration of more than two orders of magnitude is possible.
Original languageEnglish
Publication date2022
Number of pages1
Publication statusPublished - 2022
Event22nd IACM Computational Fluids Conference - Palais des Festivals et de Congrès, Cannes, France
Duration: 25 Apr 202328 Apr 2023
https://cfc2023.iacm.info/

Conference

Conference22nd IACM Computational Fluids Conference
LocationPalais des Festivals et de Congrès
Country/TerritoryFrance
CityCannes
Period25/04/202328/04/2023
Internet address

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