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Particulate Stokesian flows describe the hydrodynamics of rigid or deformable particles in Stokes flows. Due to highly nonlinear fluid-structure interaction dynamics, moving interfaces, and multiple scales, numerical simulations of such…

Computational Physics · Physics 2019-07-03 Gokberk Kabacaoglu , George Biros

We present a loosely-coupled partitioned scheme for a benchmark problem in fluid-composite structure interaction. The benchmark problem proposed here consists of an incompressible, viscous fluid interacting with a composite structure that…

Numerical Analysis · Mathematics 2015-06-18 Martina Bukac , Suncica Canic , Boris Muha

We report a novel physics-informed neural framework for reconstructing unsteady fluid-structure interactions (FSI) from sparse, single-phase observations of the flow. Our approach combines a modal surface model with coordinate neural…

Fluid Dynamics · Physics 2026-04-07 Rui Tang , Ke Zhou , Jifu Tan , Samuel J. Grauer

High-fidelity physics simulations are powerful tools in the design and optimization of charged particle accelerators. However, the computational burden of these simulations often limits their use in practice for design optimization and…

Accelerator Physics · Physics 2020-04-15 Auralee Edelen , Nicole Neveu , Yannick Huber , Mattias Frey , Christopher Mayes , Andreas Adelmann

In this effort we propose a data-driven learning framework for reduced order modeling of fluid dynamics. Designing accurate and efficient reduced order models for nonlinear fluid dynamic problems is challenging for many practical…

Computational Physics · Physics 2018-12-05 Xuping Xie , Guannan Zhang , Clayton G. Webster

Solving flow through porous media is a crucial step in the topology optimisation of cold plates, a key component in modern thermal management. Traditional computational fluid dynamics (CFD) methods, while accurate, are often prohibitively…

Fluid Dynamics · Physics 2026-03-10 Jinhong Wang , Matei C. Ignuta-Ciuncanu , Ricardo F. Martinez-Botas , Teng Cao

A stable partitioned algorithm for coupling incompressible flows with compressible elastic solids is described. This added-mass partitioned (AMP) scheme requires no sub-iterations, can be made fully second- or higher-order accurate, and…

Numerical Analysis · Mathematics 2013-08-28 J. W. Banks , W. D. Henshaw , D. W. Schwendeman

We present a new model and a novel loosely coupled partitioned numerical scheme modeling fluid-structure interaction (FSI) in blood flow allowing non-zero longitudinal displacement. Arterial walls are modeled by a {linearly viscoelastic,…

Numerical Analysis · Mathematics 2015-06-05 Martina Bukac , Suncica Canic , Roland Glowinski , Josip Tambaca , Annalisa Quaini

Finite element methods and kinematically coupled schemes that decouple the fluid velocity and structure displacement have been extensively studied for incompressible fluid-structure interaction (FSI) over the past decade. While these…

Numerical Analysis · Mathematics 2023-12-13 Buyang Li , Weiwei Sun , Yupei Xie , Wenshan Yu

Three-field Fluid-Structure Interaction (FSI) formulations for fluid and solid are applied and compared to the standard two field-one field formulation for fluid and solid, respectively. Both formulations are applied in a non linear setting…

Numerical Analysis · Mathematics 2020-10-13 Alexis Tello , Ramon Codina

A stable partitioned algorithm is developed for fluid-structure interaction (FSI) problems involving viscous incompressible flow and rigid bodies. This {\em added-mass partitioned} (AMP) algorithm remains stable, without sub-iterations, for…

Numerical Analysis · Mathematics 2017-06-07 J. W. Banks , W. D. Henshaw , D. W. Schwendeman , Qi Tang

Fluid-structure interaction (FSI) problems are pervasive in the computational engineering community. The need to address challenging FSI problems has led to the development of a broad range of numerical methods addressing a variety of…

Numerical Analysis · Mathematics 2024-09-23 Andreas Hessenthaler , Maximilian Balmus , Oliver Röhrle , David Nordsletten

For simulating incompressible flows by projection methods. it is generally accepted that the pressure-correction stage is the most time-consuming part of the flow solver. The objective of the present work is to develop a fast hybrid…

Fluid Dynamics · Physics 2023-06-05 Jiannong Fang

The design of microfluidic devices is a cumbersome and tedious process that can be significantly improved by simulation. Methods based on Computational Fluid Dynamics (CFD) are considered state-of-the-art, but require extensive compute time…

Computational Engineering, Finance, and Science · Computer Science 2024-01-17 Michel Takken , Robert Wille

Incorporating computational fluid dynamics in the design process of jets, spacecraft, or gas turbine engines is often challenged by the required computational resources and simulation time, which depend on the chosen physics-based…

Computational Physics · Physics 2019-12-09 Cristina White , Daniela Ushizima , Charbel Farhat

A new consistent, spatially adaptive, smoothed particle hydrodynamics (SPH) method for Fluid-Structure Interactions (FSI) is presented. The method combines several attributes that have not been simultaneously satisfied by other SPH methods.…

Fluid Dynamics · Physics 2019-02-20 Wei Hu , Guannan Guo , Xiaozhe Hu , Dan Negrut , Zhijie Xu , Wenxiao Pan

Solving partial differential equations (PDEs) by numerical methods meet computational cost challenge for getting the accurate solution since fine grids and small time steps are required. Machine learning can accelerate this process, but…

Numerical Analysis · Mathematics 2025-01-28 Qi Wang , Yuan Mi , Haoyun Wang , Yi Zhang , Ruizhi Chengze , Hongsheng Liu , Ji-Rong Wen , Hao Sun

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

Fluid-solid interaction (FSI) problems are fundamental in many scientific and engineering applications, yet effectively capturing the highly nonlinear two-way interactions remains a significant challenge. Most existing deep learning methods…

Machine Learning · Computer Science 2026-03-03 Shilong Tao , Zhe Feng , Shaohan Chen , Weichen Zhang , Zhanxing Zhu , Yunhuai Liu

Modern techniques for physical simulations rely on numerical schemes and mesh-refinement methods to address trade-offs between precision and complexity, but these handcrafted solutions are tedious and require high computational power.…

Machine Learning · Computer Science 2024-02-21 Janny Steeven , Nadri Madiha , Digne Julie , Wolf Christian