A novel artificial neural network-based interface coupling approach for partitioned fluid–structure interaction problems

Farrukh Mazhar*, Ali Javed, Atakan Altinkaynak

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Özet

This paper presents a novel interface technique employing Artificial Neural Networks (ANN) for efficient data transfer between incompressible fluid and deformable solid domains in a partitioned fluid–structure interaction (FSI) framework. Governing differential equations (GDE) with potential flow assumptions are solved to obtain pressure values at computational nodes in the fluid domain. Pressure values are then used to train an ANN-based model to interpolate pressure loads for application at non-collocated nodes on the solid boundary. Both finite element method (FEM) and meshfree element free Galerkin (EFG) formulations are used to calculate the solid deformation. Proposed methodology is applied to solve a two-dimensional (2D) unidirectional flow problem, consisting of a flexible cantilever beam immersed in a laminar, steady, and inviscid fluid. Overwhelming mathematical intricacies of computational solvers are avoided for the sake of simplistic interface treatment, flux transfer and associated phenomena. Dedicated partitioned solvers are developed for both solid and fluid domains, which are individually benchmarked for established problems from the literature. The presented ANN-based interpolation scheme provides an alternative to higher-order polynomial algorithms at the interface boundary. The proposed scheme is simple to employ, computationally efficient, and offers competitive accuracy as well as stability.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)287-308
Sayfa sayısı22
DergiEngineering Analysis with Boundary Elements
Hacim151
DOI'lar
Yayın durumuYayınlandı - Haz 2023

Bibliyografik not

Publisher Copyright:
© 2023 Elsevier Ltd

Finansman

Authors would like to acknowledge all associated support provided by Istanbul Technical University, Turkiye , Turkiye Burslari Program, Govt of Turkey, National University of Sciences and Technology, Pakistan and Higher Education Commission, Pakistan . We also acknowledge the assistance and guidance provided by Prof. Dr. I. Bedii Ozdemir, Istanbul Technical University, Istanbul, Turkiye and the numerous online programming libraries, resources, and supporting materials that have been helpful in concluding this research.

FinansörlerFinansör numarası
National University of Sciences and Technology, Pakistan and Higher Education Commission, Pakistan
Istanbul Teknik Üniversitesi

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