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Our paper proposes an innovative approach for modeling Fluid-Structure Interaction (FSI). Our method combines both traditional monolithic and partitioned approaches, creating a hybrid solution that facilitates FSI. At each time iteration,…

Numerical Analysis · Mathematics 2024-01-15 R. Nemer , A. Larcher , E. Hachem

Vision-language-action (VLA) models remain constrained by the scarcity of action-labeled robot data, whereas action-free videos provide abundant evidence of how the physical world changes. Latent action models offer a promising way to…

Most Video Super-Resolution (VSR) methods enhance a video reference frame by aligning its neighboring frames and mining information on these frames. Recently, deformable alignment has drawn extensive attention in VSR community for its…

Computer Vision and Pattern Recognition · Computer Science 2021-05-13 Jiayi Lin , Yan Huang , Liang Wang

We present a novel framework inspired by the Immersed Boundary Method for predicting the fluid-structure interaction of complex structures immersed in flows with moderate to high Reynolds numbers. The main novelties of the proposed…

Within this work, we consider optimization settings for nonlinear, nonstationary fluid-structure interaction. The problem is formulated in a monolithic fashion using the arbitrary Lagrangian-Eulerian framework to set-up the fluid-structure…

Numerical Analysis · Mathematics 2020-06-29 Thomas Wick , Winnifried Wollner

We propose an explicit partitioned (loosely coupled) scheme for fluid structure interaction (FSI) problems, specifically designed to achieve high computational efficiency in modern engineering simulations. The FSI problem under…

Numerical Analysis · Mathematics 2025-10-16 Shihan Guo , Ping Lin , Yifan Wang , Xiaohe Yue , Haibiao Zheng

Fast and accurate predictions of turbulent flows are of great importance in the science and engineering field. In this paper, we investigate the implicit U-Net enhanced Fourier neural operator (IUFNO) in the stable prediction of long-time…

Fluid Dynamics · Physics 2024-11-05 Yunpeng Wang , Zhijie Li , Zelong Yuan , Wenhui Peng , Tianyuan Liu , Jianchun Wang

We present a novel second-order semi-implicit hybrid finite volume / finite element (FV/FE) scheme for the numerical solution of the incompressible and weakly compressible Navier-Stokes equations on moving unstructured meshes using an…

Numerical Analysis · Mathematics 2023-01-24 Saray Busto , Michael Dumbser , Laura Río-Martín

We present an adaptive reduced-order model for the efficient time-resolved simulation of fluid-structure interaction problems with complex and non-linear deformations. The model is based on repeated linearizations of the structural balance…

Fluid Dynamics · Physics 2020-04-13 Ali Thari , Vito Pasquariello , Niels Aage , Stefan Hickel

A new geometrically conservative arbitrary Lagrangian-Eulerian (ALE) formulation is presented for the moving boundary problems in the swirl-free cylindrical coordinates. The governing equations are multiplied with the radial distance and…

Fluid Dynamics · Physics 2010-10-22 Mehmet Sahin , Kamran Mohseni

This study presents the development of a compact gas-kinetic scheme using an arbitrary Lagrangian-Eulerian (ALE) formulation for structured meshes. Unlike the Eulerian formulation, the ALE approach effectively tracks flow discontinuities,…

Computational Physics · Physics 2026-02-11 Yue Zhang , Xing Ji , Yibing Chen , Fengxiang Zhao , Kun Xu

Computational fluid dynamics (CFD) provides high-fidelity simulations of fluid flows but remains computationally expensive for many-query applications. In recent years deep learning (DL) has been used to construct data-driven fluid-dynamic…

Machine Learning · Computer Science 2026-04-13 David Ramos , Lucas Lacasa , Fermín Gutiérrez , Eusebio Valero , Gonzalo Rubio

AFSI is a novel, open-source fluid-structure interaction (FSI) solver that extends the capabilities of the FEniCS finite element library through an immersed boundary (IB) framework. Designed to simulate large deformations in hyperelastic…

Computational Physics · Physics 2025-09-03 Pengfei Ma , Li Cai , Xuan Wang , Hao Gao

We present a partitioned neural network-based framework for learning of fluid-structure interaction (FSI) problems. We decompose the simulation domain into two smaller sub-domains, i.e., fluid and solid domains, and incorporate an…

Computational Engineering, Finance, and Science · Computer Science 2021-05-17 Amin Totounferoush , Axel Schumacher , Miriam Schulte

Operational flood forecasting still relies on high-fidelity two-dimensional hydraulic solvers, but their runtime can be prohibitive for rapid decision support on large urban floodplains. In parallel, AI-based surrogate models have shown…

Machine Learning · Computer Science 2026-04-06 Valentin Mercier , Serge Gratton , Lapeyre Corentin , Gwenaël Chevallet

Aquatic locomotion is a classic fluid-structure interaction (FSI) problem of interest to biologists and engineers. Solving the fully coupled FSI equations for incompressible Navier-Stokes and finite elasticity is computationally expensive.…

An interface control principle is proposed for unsteady fluid-structure in- teraction (FSI) analyses. This principle introduces a method of explicitly controlling the interface motion in the temporal direction to minimize the residual force…

Fluid Dynamics · Physics 2025-10-21 Chungil Lee , Yoshiaki Abe , Yu Kawano , Tomoki Yamazaki

We present a fully-integrated lattice Boltzmann (LB) method for fluid--structure interaction (FSI) simulations that efficiently models deformable solids in complex suspensions and active systems. Our Eulerian method (LBRMT) couples…

Fluid Dynamics · Physics 2024-02-21 Yue Sun , Chris H. Rycroft

The governing equations and numerical solution strategy to solve porohyperelastic problems as multiscale multiphysics media are provided in this contribution. The problem starts from formulating and non-dimensionalising a Fluid-Solid…

Computational Engineering, Finance, and Science · Computer Science 2023-02-22 Hamidreza Dehghani , Andreas Zilian

Reliable long-horizon prediction remains a challenge for data-driven CFD surrogates, because offline-trained models accumulate autoregressive errors and lose accuracy when operating conditions change. This work develops a divergence-aware…

Fluid Dynamics · Physics 2026-05-26 Xiangrui Zou , Zhuoqun Zhao , Guillermo Barragán , Soledad Le Clainche