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Accurate prediction of permeability in porous media is essential for modeling subsurface flow. While pure data-driven models offer computational efficiency, they often lack generalization across scales and do not incorporate explicit…

Machine Learning · Computer Science 2025-09-18 Qingqi Zhao , Heng Xiao

Fast prediction of suspension rheology is fundamental for optimizing process efficiency and performance in numerous industrial settings. However, traditional simulations are computationally demanding due to explicit evaluation of contact…

Soft Condensed Matter · Physics 2026-02-10 Armin Aminimajd , Joao Maia , Abhinendra Singh

This paper reviews the current state-of-the-art in the simulation of the mechanical behavior of polycrystalline materials by means of computational homogenization. The key ingredients of this modelling strategy are presented in detail…

Materials Science · Physics 2018-11-22 J. Segurado , R. A. Lebensohn , J. LLorca

Scene coordinate regression (SCR) methods are a family of visual localization methods that directly regress 2D-3D matches for camera pose estimation. They are effective in small-scale scenes but face significant challenges in large-scale…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Fangjinhua Wang , Xudong Jiang , Silvano Galliani , Christoph Vogel , Marc Pollefeys

Nanoindentation is a convenient method to investigate the mechanical properties of materials on small scales by utilizing low loads and small indentation depths. However, the effect of grain boundaries (GB) on the nanoindentation response…

Materials Science · Physics 2019-03-27 Songjiang Lu , Bo Zhang , Xiangyu Li , Junwen Zhao , Michael Zaiser , Haidong Fan , Xu Zhang

Accurate large-scale Kohn-Sham density functional theory (DFT) calculations are essential for modeling complex material systems, including interfaces, defects, nanoclusters, and twisted two-dimensional heterostructures. Achieving chemical…

Computational Physics · Physics 2026-04-30 Kartick Ramakrishnan , Phani Motamarri

We present a Graph Neural Network (GNN) that accurately simulates a multidisperse suspension of interacting spherical particles. Our machine learning framework is built upon the recent work of Sanchez-Gonzalez et al. ICML, PMLR, 119,…

Computational Physics · Physics 2025-02-20 Aref Hashemi , Aliakbar Izadkhah

Dislocation mobility, which dictates the response of dislocations to an applied stress, is a fundamental property of crystalline materials that governs the evolution of plastic deformation. Traditional approaches for deriving mobility laws…

Computational fluid dynamics (CFD) simulations are crucial in automotive, aerospace, maritime and medical applications, but are limited by the complexity, cost and computational requirements of directly calculating the flow, often taking…

Machine Learning · Computer Science 2024-11-27 Zachary Cooper-Baldock , Paulo E. Santos , Russell S. A. Brinkworth , Karl Sammut

A two-dimensional (2D) dislocation continuum theory is being introduced. The present theory adds elastic rotation, dislocation density, and background stress to the classical energy density of elasticity. This theory contains four material…

Mesoscale and Nanoscale Physics · Physics 2015-10-15 Markus Lazar

In this paper, we propose a new Deep Neural Network (DNN) testing algorithm called the Constrained Gradient Descent (CGD) method, and an implementation we call CGDTest aimed at exposing security and robustness issues such as adversarial…

Machine Learning · Computer Science 2023-04-05 Vineel Nagisetty , Laura Graves , Guanting Pan , Piyush Jha , Vijay Ganesh

Propagation characteristics of a wave are defined by the dispersion relationship, from which the governing partial differential equation (PDE) can be recovered. PDEs are commonly solved numerically using the finite-difference (FD) method,…

Numerical Analysis · Mathematics 2021-07-29 Edward Caunt

The goal of this paper is to develop and analyze some fully discrete finite element methods for a displacement-pressure model modeling swelling dynamics of polymer gels under mechanical constraints. In the model, the swelling dynamics is…

Numerical Analysis · Mathematics 2009-03-25 Xiaobing Feng , Yinnian He

Dense suspensions often exhibit shear thickening, characterized by a dramatic increase in viscosity under large external forcing. This behavior has recently been linked to the formation of a system-spanning frictional contact network (FCN),…

Soft Condensed Matter · Physics 2025-02-04 Armin Aminimajd , Joao Maia , Abhinendra Singh

Global Climate Models (GCMs) are numerical models that simulate complex physical processes within the Earth's climate system and are essential for understanding and predicting climate change. However, GCMs suffer from systemic biases due to…

Applications · Statistics 2026-02-23 Reetam Majumder , Shiqi Fang , A. Sankarasubramanian , Emily C. Hector , Brian J. Reich

Synchrotron Laue microdiffraction and Digital Image Correlation measurements were coupled to track the elastic strain field (or stress field) and the total strain field near a general grain boundary in a bent bicrystal. A 316L stainless…

In this work, we employ the Constraint Energy Minimizing Generalized Multiscale Finite Element Method (CEM-GMsFEM) to solve the problem of linear heterogeneous poroelasticity with coefficients of high contrast. The proposed method makes use…

Numerical Analysis · Mathematics 2019-09-04 Shubin Fu , Robert Altmann , Eric T. Chung , Roland Maier , Daniel Peterseim , Sai-Mang Pun

Crystal plasticity is the result of the motion and interaction of dislocations. There is, however, still a major gap between microscopic and mesoscopic simulations and continuum crystal plasticity models. Only recently a higher dimensional…

Materials Science · Physics 2010-10-15 Thomas Hochrainer , Michael Zaiser , Peter Gumbsch

Accurate and smooth global navigation satellite system (GNSS) positioning for pedestrians in urban canyons is still a challenge due to the multipath effects and the non-light-of-sight (NLOS) receptions caused by the reflections from…

Robotics · Computer Science 2024-05-08 Yihan Zhong , Weisong Wen , Li-Ta Hsu

Aims. Our aim is to derive a fast and accurate method for computing the gravitational potential of astrophysical objects with high contrasts in density, for which nested or adaptive meshes are required. Methods. We present an extension of…

Solar and Stellar Astrophysics · Physics 2023-03-15 Eduard Vorobyov , James McKevitt , Igor Kulikov , Vardan Elbakyan