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This paper describes a 2D and 3D simulation engine that quantitatively models the statics, dynamics, and non-linear deformation of heterogeneous soft bodies in a computationally efficient manner. There is a large body of work simulating…

Graphics · Computer Science 2012-12-13 Jonathan Hiller , Hod Lipson

Physical simulation predicts future states of objects based on material properties and external loads, enabling blueprints for both Industry and Engineering to conduct risk management. Current 3D reconstruction-based simulators typically…

Machine Learning · Computer Science 2026-02-20 Yicheng Cao , Zhuo Huang , Yu Yao , Yiming Ying , Daoyi Dong , Tongliang Liu

Here we present a machine learning framework and model implementation that can learn to simulate a wide variety of challenging physical domains, involving fluids, rigid solids, and deformable materials interacting with one another. Our…

Machine Learning · Computer Science 2020-09-15 Alvaro Sanchez-Gonzalez , Jonathan Godwin , Tobias Pfaff , Rex Ying , Jure Leskovec , Peter W. Battaglia

We develop numerical methods to simulate the fluid-mechanical erosion of many bodies in two-dimensional Stokes flow. The broad aim is to simulate the erosion of a porous medium (e.g. groundwater flow) with grain-scale resolution. Our fluid…

Numerical Analysis · Mathematics 2018-09-26 Bryan D. Quaife , M. Nicholas J. Moore

In this paper, we introduce a unified framework for nonlinear Krylov subspace methods (nlKrylov) to solve systems of nonlinear equations. Building on classical GCR-like/type linear Krylov solvers such as GMRESR, we generalize these…

Numerical Analysis · Mathematics 2025-11-19 Tom Werner , Ning Wan , Agnieszka Miedlar

Recently, Gaussian Splatting (GS) has received a lot of attention in surface reconstruction. However, while 3D objects can be of complex and diverse shapes in the real world, existing GS-based methods only limitedly use a single type of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Haoxuan Qu , Yujun Cai , Hossein Rahmani , Ajay Kumar , Junsong Yuan , Jun Liu

A computational approach is introduced for the study of the rheological properties of complex fluids and soft materials. The approach allows for a consistent treatment of microstructure elastic mechanics, hydrodynamic coupling, thermal…

Soft Condensed Matter · Physics 2023-02-28 P. J. Atzberger

In this paper, we describe a soil-fluid-structure interaction model that combines soil mechanics (saturated sediments), fluid mechanics (seawater or air), and solid mechanics (structures). The formulation combines the Material Point Method,…

Numerical Analysis · Mathematics 2022-11-24 Quoc Anh Tran , Gustav Grimstad , Seyed Ali Ghoreishian Amiri

A second-order accurate and robust numerical scheme is developed for the Kapila model to simulate compressible multiphase flows. The scheme is formulated within the finite volume framework with the generalized Riemann problem (GRP) solver…

Numerical Analysis · Mathematics 2025-06-10 Tuowei Chen , Zhifang Du

This paper develops and benchmarks an immersed peridynamics method to simulate the deformation, damage, and failure of hyperelastic materials within a fluid-structure interaction framework. The immersed peridynamics method describes an…

Numerical Analysis · Mathematics 2023-10-19 Keon Ho Kim , Amneet P. S. Bhalla , Boyce E. Griffith

A high-resolution Eulerian method for simulating high-speed polydisperse granular multiphase flows has been developed. The governing equations include a compressible gas that is coupled to mass-based moment equations for a polydisperse…

Fluid Dynamics · Physics 2026-03-17 Jacob W. Posey , Rodney O. Fox , Ryan W. Houim

The current work presents a novel COllaborative Open-source Lattice Boltzmann Method framework, so-called CooLBM. The computational framework is developed for the simulation of single and multi-component multi-phase problems, along with a…

Computational Physics · Physics 2025-02-19 R. Alamian , A. K. Nayak , M. S. Shadloo

We propose a computational framework for vascular fluid-structure interaction (FSI), focusing on biomechanical modeling, geometric modeling, and solver technology. The biomechanical model is constructed based on the unified continuum…

Fluid Dynamics · Physics 2022-06-27 Ju Liu , Jiayi Huang , Qingshuang Lu , Yujie Sun

Godunov-type methods, which obtain numerical fluxes through local Riemann problems at cell interfaces, are among the most fundamental and widely used numerical methods in computational fluid dynamics. Exact Riemann solvers faithfully solve…

Computational Physics · Physics 2026-04-01 Yucheng Zhang , Chayanon Wichitrnithed , Shukai Cai , Sourav Dutta , Kyle Mandli , Clint Dawson

The material point method (MPM), a hybrid Lagrangian-Eulerian particle method, is increasingly used to simulate large-deformation and history-dependent behavior of geomaterials. While explicit time integration dominates current MPM…

Computational Engineering, Finance, and Science · Computer Science 2025-12-30 Yidong Zhao , Xuan Li , Chenfanfu Jiang , Jinhyun Choo

One obstacle to the use of Gaussian processes (GPs) in large-scale problems, and as a component in deep learning system, is the need for bespoke derivations and implementations for small variations in the model or inference. In order to…

Machine Learning · Statistics 2020-03-04 Mark van der Wilk , Vincent Dutordoir , ST John , Artem Artemev , Vincent Adam , James Hensman

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…

We developed a computational framework for simulating thin fluid flow in narrow interfaces between contacting solids, which is relevant for a range of engineering, biological and geophysical applications. The treatment of this problem…

Computational Engineering, Finance, and Science · Computer Science 2021-03-23 Andrei G. Shvarts , Julien Vignollet , Vladislav A. Yastrebov

This paper presents a unified framework, called multiRegionFoam, for solving multiphysics problems of the multi-region coupling type within OpenFOAM (FOAM-extend). It is intended to supersede the existing solver with the same name. The…

We propose Riemannian Flow Matching (RFM), a simple yet powerful framework for training continuous normalizing flows on manifolds. Existing methods for generative modeling on manifolds either require expensive simulation, are inherently…

Machine Learning · Computer Science 2024-02-27 Ricky T. Q. Chen , Yaron Lipman
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