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Related papers: CRESSim-MPM: A Material Point Method Library for S…

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Data driven approaches have the potential to make modeling complex, nonlinear physical phenomena significantly more computationally tractable. For example, computational modeling of fracture is a core challenge where machine learning…

Machine Learning · Computer Science 2025-10-01 Erfan Hamdi , Emma Lejeune

Mixtures of fluids and granular sediments play an important role in many industrial, geotechnical, and aerospace engineering problems, from waste management and transportation (liquid--sediment mixtures) to dust kick-up below helicopter…

Computational Engineering, Finance, and Science · Computer Science 2021-07-07 Aaron S. Baumgarten , Benjamin L. S. Couchman , Ken Kamrin

An important challenge in robotics is understanding the interactions between robots and deformable terrains that consist of granular material. Granular flows and their interactions with rigid bodies still pose several open questions. A…

Machine Learning · Computer Science 2021-11-22 Amin Haeri , Krzysztof Skonieczny

The recent evolution of software and hardware technologies is leading to a renewed computational interest in Particle-In-Cell (PIC) methods such as the Material Point Method (MPM). Indeed, provided some critical aspects are properly…

Computational Physics · Physics 2024-12-11 Paolo Joseph Baioni , Tommaso Benacchio , Luigi Capone , Carlo de Falco

The Fragile Points Method (FPM) is an elementarily simple Galerkin meshless method, employing Point-based discontinuous trial and test functions only, without using element-based trial and test functions. In this study, the algorithmic…

Numerical Analysis · Mathematics 2020-11-26 Tian Yang , Leiting Dong , Satya N. Atluri

The performance evaluation of a potentially unstable slope involves two key components: the initiation of the slope failure and the post-failure runout. The Finite Element Method (FEM) excels at modeling the initiation of instability but…

Geophysics · Physics 2022-06-16 Brent Sordo , Ellen Rathje , Krishna Kumar

Accurate and efficient modeling of soft-tissue interactions is fundamental for advancing surgical simulation, surgical robotics, and model-based surgical automation. To achieve real-time latency, classical Finite Element Method (FEM)…

Accurate deformable object manipulation (DOM) is essential for achieving autonomy in robotic surgery, where soft tissues are being displaced, stretched, and dissected. Many DOM methods can be powered by simulation, which ensures realistic…

Robotics · Computer Science 2024-05-31 Xiao Liang , Fei Liu , Yutong Zhang , Yuelei Li , Shan Lin , Michael Yip

The simulation of high-rate deformation and failure of metals is has traditionally been performed using Lagrangian finite element methods or Eulerian hydrocodes. Lagrangian mesh-based methods are limited by issues involving mesh…

Computational Physics · Physics 2012-01-13 Biswajit Banerjee , James E. Guilkey , Todd B. Harman , John A. Schmidt , Patrick A. McMurtry

In this paper, we describe a new scalable and modular material point method (MPM) code developed for solving large-scale problems in continuum mechanics. The MPM is a hybrid Eulerian-Lagrangian approach, which uses both moving material…

We present the AMPS algorithm, a finite element solution method that combines principal submatrix updates and Schur complement techniques, well-suited for interactive simulations of deformation and cutting of finite element meshes. Our…

Computational Engineering, Finance, and Science · Computer Science 2018-11-02 Yu-Hong Yeung , Alex Pothen , Jessica Crouch

Robotic cutting of soft materials is critical for applications such as food processing, household automation, and surgical manipulation. As in other areas of robotics, simulators can facilitate controller verification, policy learning, and…

Robotics · Computer Science 2021-05-27 Eric Heiden , Miles Macklin , Yashraj Narang , Dieter Fox , Animesh Garg , Fabio Ramos

Surgical robot simulation platform plays a crucial role in enhancing training efficiency and advancing research on robot learning. Much effort have been made by scholars on developing open-sourced surgical robot simulators to facilitate…

Robotics · Computer Science 2024-02-05 Zhenya Yang , Yonghao Long , Kai Chen , Wang Wei , Qi Dou

This work presents an approach for automating the discretization and approximation procedures in constructing digital representations of composites from Micro-CT images featuring intricate microstructures. The proposed method is guided by…

Machine Learning · Computer Science 2025-09-11 Yanran Wang , Jonghyuk Baek , Yichun Tang , Jing Du , Mike Hillman , J. S. Chen

Numerical modeling of slope failures seeks to predict two key phenomena: the initiation of failure and the post-failure runout. Currently, most modeling methods for slope failure analysis excel at one of these two but are deficient in the…

Numerical Analysis · Mathematics 2024-07-09 Brent Sordo , Ellen Rathje , Krishna Kumar

Intraoperative observation of tissue internal structure is often difficult. Hence, real-time soft tissue deformation is essential for the localization of tumor and other internal structures. We propose a method to simulate the internal…

Computational Geometry · Computer Science 2019-07-26 Haoyin Zhou , Eva Gombos , Mehra Golshan , Jayender Jagadeesan

High-accuracy, high-efficiency physics-based fluid-solid interaction is essential for reality modeling and computer animation in online games or real-time Virtual Reality (VR) systems. However, the large-scale simulation of incompressible…

Graphics · Computer Science 2023-05-08 Jin Li , Yang Gao , Ju Dai , Shuai Li , Aimin Hao , Hong Qin

Robotic cutting of soft materials is critical for applications such as food processing, household automation, and surgical manipulation. As in other areas of robotics, simulators can facilitate controller verification, policy learning, and…

Robotics · Computer Science 2022-03-22 Eric Heiden , Miles Macklin , Yashraj Narang , Dieter Fox , Animesh Garg , Fabio Ramos

Learning the physical simulation on large-scale meshes with flat Graph Neural Networks (GNNs) and stacking Message Passings (MPs) is challenging due to the scaling complexity w.r.t. the number of nodes and over-smoothing. There has been…

Machine Learning · Computer Science 2026-05-27 Yadi Cao , Menglei Chai , Minchen Li , Chenfanfu Jiang

This paper introduces BFEMP, a new approach for monolithically coupling the Material Point Method (MPM) with the Finite Element Method (FEM) through barrier energy-based particle-mesh frictional contact using a variational time-stepping…

Numerical Analysis · Mathematics 2022-02-02 Xuan Li , Yu Fang , Minchen Li , Chenfanfu Jiang