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The aim of this paper is to propose a novel methodology to deal with micro-structural boundary conditions for the analysis of granular materials. The response of the granular assembly is modelled through the discrete element method (DEM),…

Soft Condensed Matter · Physics 2017-02-27 J. Liu , E. Bosco , A. S. J. Suiker

We present a finite element-inspired hypergraph neural network framework for predicting flow-induced vibrations in freely oscillating cylinders. The surrogate architecture transforms unstructured computational meshes into node-element…

Fluid Dynamics · Physics 2025-07-04 Shayan Heydari , Rui Gao , Rajeev K Jaiman

Using the volume averaging technique of Jackson (1997), we derive a set of two-fluid equations that describe the dynamics of a mono-disperse non-Brownian colloidal suspension in the semi-dilute regime. The equations are tensorial and can be…

Fluid Dynamics · Physics 2025-01-06 Dalton J. E. Harvie

The peridynamic theory brings advantages in dealing with discontinuities, dynamic loading, and non-locality. The integro-differential formulation of peridynamics poses challenges to numerical solutions of complicated and practical problems.…

Numerical Analysis · Mathematics 2021-06-01 Xue Liang , Linjuan Wang , Jifeng Xu , Jianxiang Wang

We present our progress on the application of physics informed deep learning to reservoir simulation problems. The model is a neural network that is jointly trained to respect governing physical laws and match boundary conditions. The…

Fluid Dynamics · Physics 2021-04-26 Cedric Fraces Gasmi , Hamdi Tchelepi

We begin by addressing the time-domain full-waveform inversion using the adjoint method. Next, we derive the scaled boundary semi-weak form of the scalar wave equation in heterogeneous media through the Galerkin method. Unlike conventional…

Numerical Analysis · Mathematics 2025-01-14 Alireza Daneshyar , Stefan Kollmannsberger

The boundary element method (BEM) enables the efficient electromagnetic modelling of lossy conductors with a surface-based discretization. Existing BEM techniques for conductor modelling require either expensive dual basis functions or the…

Computational Physics · Physics 2020-12-29 Shashwat Sharma , Piero Triverio

We are interested in time-harmonic acoustic scattering by an impenetrable obstacle in a medium where the wavenumber is constant in an exterior unbounded subdomain and is possibly heterogeneous in a bounded subdomain. The associated…

Numerical Analysis · Mathematics 2025-12-15 Antonin Boisneault , Marcella Bonazzoli , Pierre Marchand , Xavier Claeys

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

Predicting the rheological behavior of associative polymers bridging colloidal particles into transient networks is fundamentally challenging because the coupled spatiotemporal scales prevent efficient molecular-fidelity modeling. We…

Soft Condensed Matter · Physics 2026-02-17 Jalal Abdolahi , Dominic M. Robe , Ronald G. Larson , Elnaz Hajizadeh

In this paper, we consider a pressure-velocity formulation of the heterogeneous wave equation and employ the constraint energy minimizing generalized multiscale finite element method (CEM-GMsFEM) to solve this problem. The proposed method…

Numerical Analysis · Mathematics 2020-10-06 Eric Chung , Sai-Mang Pun

Understanding the dynamics of phase boundaries in fluids requires quantitative knowledge about the microscale processes at the interface. We consider the sharp-interface motion of compressible two-component flow, and propose a heterogeneous…

Numerical Analysis · Mathematics 2023-09-06 Jim Magiera , Christian Rohde

Real-time simulation of elastic structures is essential in many applications, from computer-guided surgical interventions to interactive design in mechanical engineering. The Finite Element Method is often used as the numerical method of…

Machine Learning · Computer Science 2021-09-21 Alban Odot , Ryadh Haferssas , Stéphane Cotin

We present a unified hard-constraint framework for solving geometrically complex PDEs with neural networks, where the most commonly used Dirichlet, Neumann, and Robin boundary conditions (BCs) are considered. Specifically, we first…

Machine Learning · Computer Science 2023-06-06 Songming Liu , Zhongkai Hao , Chengyang Ying , Hang Su , Jun Zhu , Ze Cheng

We evaluate an efficient overset grid method for two-dimensional and three-dimensional particulate flows for small numbers of particles at finite Reynolds number. The rigid particles are discretised using moving overset grids overlaid on a…

Computational Physics · Physics 2017-05-24 A. R. Koblitz , S. Lovett , N. Nikiforakis , W. D. Henshaw

Weakly-compressible particle-based discretization methods, utilized for the solution of the subsonic Navier-Stokes equation, are gaining increasing popularity in the fluid dynamics community. One of the most popular among these methods is…

Fluid Dynamics · Physics 2021-08-18 Max Okraschevski , Niklas Buerkle , Rainer Koch , Hans-Joerg Bauer

An efficient and accurate finite-element algorithm is described for the numerical solution of the incompressible Navier-Stokes (INS) equations. The new algorithm that solves the INS equations in a velocity-pressure reformulation is based on…

Numerical Analysis · Mathematics 2020-02-19 Longfei Li

First, a meshless simulation method is presented for multiphase fluid-particle flows with a two-way coupled Smoothed Particle Hydrodynamics (SPH) for the fluid and the Discrete Element Method (DEM) for the solid phase. The unresolved fluid…

Fluid Dynamics · Physics 2014-02-28 Martin Robinson , Stefan Luding , Marco Ramaioli

The rapid expansion of electric vehicles has intensified the need for accurate and efficient diagnosis of lithium-ion batteries. Parameter identification of electrochemical battery models is widely recognized as a powerful method for…

Machine Learning · Computer Science 2025-10-29 Hojin Cheon , Hyeongseok Seo , Jihun Jeon , Wooju Lee , Dohyun Jeong , Hongseok Kim

When using the finite element method (FEM) in inverse problems, its discretization error can produce parameter estimates that are inaccurate and overconfident. The Bayesian finite element method (BFEM) provides a probabilistic model for the…

Numerical Analysis · Mathematics 2026-01-26 Anne Poot , Iuri Rocha , Pierre Kerfriden , Frans van der Meer