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A brief summary of direct solution approaches for finite element methods (FEM) in computational electromagnetics (CEM) is given along with an alternative direct solution based on domain decomposition (DD). Unlike recent trends in…

Computational Engineering, Finance, and Science · Computer Science 2020-02-13 Javad Moshfegh , Marinos N. Vouvakis

We propose a Pretrained Finite Element Method (PFEM),a physics driven framework that bridges the efficiency of neural operator learning with the accuracy and robustness of classical finite element methods (FEM). PFEM consists of a physics…

This work provides an efficient virtual element scheme for the modeling of nonlinear elastodynamics undergoing large deformations. The virtual element method (VEM) has been applied to various engineering problems such as elasto-plasticity,…

Numerical Analysis · Mathematics 2020-02-10 M. Cihan , F. Aldakheel , B. Hudobivnik , P. Wriggers

We propose a method for efficiently coupling the finite element method with atomistic simulations, while using molecular dynamics or kinetic Monte Carlo techniques. Our method can dynamically build an optimized unstructured mesh that…

Computational Engineering, Finance, and Science · Computer Science 2018-05-23 Mihkel Veske , Andreas Kyritsakis , Kristjan Eimre , Vahur Zadin , Alvo Aabloo , Flyura Djurabekova

The combination of Finite Element Method (FEM) simulation and experimental photo-elasticity provides both qualitative and quantitative information about the stress field in a polymer composite and particularly along the fibre-matrix…

Materials Science · Physics 2007-05-23 H. Matthias Deuschle , Falk K. Wittel , Henry Gerhard , Gerhard Busse , Bernd-H. Kroeplin

The aim of this paper is to deal with multi-physics simulation of micro-electro-mechanical systems (MEMS) based on an advanced numerical methodology. MEMS are very small devices in which electric as well as mechanical and fluid phenomena…

Other Computer Science · Computer Science 2007-11-29 V. Rochus , J. -C. Golinval , C. Louis , C. Mendez , I. Klapka

We propose a computational framework, Hetero-EUCLID, for segmentation and parameter identification to characterize the full hyperelastic behavior of all constituents of a heterogeneous material. In this work, we leverage the Bayesian-EUCLID…

Computational Engineering, Finance, and Science · Computer Science 2026-01-19 Kanhaiya Lal Chaurasiya , Saurav Dutta , Siddhant Kumar , Akshay Joshi

An innovative physics-guided learning algorithm for predicting the mechanical response of materials and structures is proposed in this paper. The key concept of the proposed study is based on the fact that physics models are governed by…

Computational Engineering, Finance, and Science · Computer Science 2020-04-22 Houpu Yao , Yi Gao , Yongming Liu

Simulation of fracturing processes in porous rocks can be divided into two main branches: (i) modeling the rock as a continuum which is enhanced with special features to account for fractures, or (ii) modeling the rock by a discrete (or…

Numerical Analysis · Mathematics 2017-02-07 Halvor Møll Nilsen , Idar Larsen , Xavier Raynaud

In various applications, such as virtual reality and gaming, simulating the deformation of soft tissues in the human body during interactions with external objects is essential. Traditionally, Finite Element Methods (FEM) have been employed…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Anton Agafonov , Lihi Zelnik-Manor

The development of novel materials in recent years has been accelerated greatly by the use of computational modelling techniques aimed at elucidating the complex physics controlling microstructure formation in materials, the properties of…

Materials Science · Physics 2025-11-14 Damien Pinto , Michael Greenwood , Nikolas Provatas

Simulating the complex interactions between soft tissues and rigid anatomy is critical for applications in surgical training, planning, and robotic-assisted interventions. Traditional Finite Element Method (FEM)-based simulations, while…

Robotics · Computer Science 2025-08-05 Xintian Yuan , Yunke Ao , Boqi Chen , Philipp Fuernstahl

Evaluating the mechanical response of fiber-reinforced composites can be extremely time consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input-output pairs and…

Materials Science · Physics 2024-10-03 Yixuan Sun , Imad Hanhan , Michael D. Sangid , Guang Lin

We propose an efficient and accurate parametric finite element method (PFEM) for solving sharp-interface continuum models for solid-state dewetting of thin films with anisotropic surface energies. The governing equations of the…

Numerical Analysis · Mathematics 2017-01-10 Weizhu Bao , Wei Jiang , Yan Wang , Quan Zhao

In this paper, we propose a way to solve partial differential equations (PDEs) by combining machine learning techniques and the finite element method called Phi-FEM. For that, we use the Fourier Neural Operator (FNO), a learning mapping…

Numerical Analysis · Mathematics 2025-03-05 Michel Duprez , Vanessa Lleras , Alexei Lozinski , Vincent Vigon , Killian Vuillemot

Recent developments in mechanical, aerospace, and structural engineering have driven a growing need for efficient ways to model and analyse structures at much larger and more complex scales than before. While established numerical methods…

Machine Learning · Computer Science 2025-07-29 Rui Wu , Nikola Kovachki , Burigede Liu

An important step in shape optimization with partial differential equation constraints is to adapt the geometry during each optimization iteration. Common strategies are to employ mesh-deformation or re-meshing, where one or the other…

Numerical Analysis · Mathematics 2018-06-27 Jorgen S. Dokken , Simon W. Funke , August Johansson , Stephan Schmidt

Partition of unity methods, such as the extended finite element method (XFEM) allow discontinuities to be simulated independently of the mesh [1]. This eliminates the need for the mesh to be aligned with the discontinuity or cumbersome…

Numerical Analysis · Mathematics 2011-07-26 Sundararajan Natarajan , D. Roy Mahapatra , Stephane PA Bordas

Physics-constrained data-driven computing is an emerging computational paradigm that allows simulation of complex materials directly based on material database and bypass the classical constitutive model construction. However, it remains…

Numerical Analysis · Mathematics 2022-09-12 Xiaolong He , Qizhi He , Jiun-Shyan Chen

We introduce the concept of data-driven finite element methods. These are finite-element discretizations of partial differential equations (PDEs) that resolve quantities of interest with striking accuracy, regardless of the underlying mesh…

Numerical Analysis · Mathematics 2022-11-15 Ignacio Brevis , Ignacio Muga , Kristoffer G. van der Zee
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