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The large time and length scales and, not least, the vast number of particles involved in industrial-scale simulations inflate the computational costs of the Discrete Element Method (DEM) excessively. Coarse grain models can help to lower…

Computational Physics · Physics 2017-05-11 Daniel Queteschiner , Thomas Lichtenegger , Simon Schneiderbauer , Stefan Pirker

Transient size segregation of a bi-disperse granular mixture flowing over a periodic chute is studied using DEM simulations and theory. A recently developed particle force-based size segregation model has been shown to successfully predict…

Soft Condensed Matter · Physics 2025-05-13 Soniya Kumawat , Anurag Tripathi

Predicting particle segregation has remained challenging due to the lack of a general model for the segregation velocity that is applicable across a range of granular flow geometries. Here, a segregation velocity model for dense granular…

Soft Condensed Matter · Physics 2025-10-22 Yifei Duan , Lu Jing , Paul B. Umbanhowar , Julio M. Ottino , Richard M. Lueptow

Evolution of mixing of granular solids in a slowly rotated 2D drum is considered as a discrete mapping. The rotation is around the axis of the upright drum which is filled partially, and the mixing occurs only at a free surface of a…

Condensed Matter · Physics 2007-05-23 S. N. Dorogovtsev

Obtaining a rigorous and reliable method for linking computer simulations of polymer blends and composites at different length scales of interest is a highly desirable goal in soft matter physics. In this paper a multiscale modeling…

Soft Condensed Matter · Physics 2015-05-19 J. McCarty , M. G. Guenza

Long simulation times in climate sciences typically require coarse grids due to computational constraints. Nonetheless, unresolved subscale information significantly influences the prognostic variables and can not be neglected for reliable…

Numerical Analysis · Mathematics 2018-02-22 Konrad Simon , Jörn Behrens

Mixing of two fractions of a granular material in a slowly rotating two-dimensional drum is considered. The rotation is around the axis of the upright drum. The drum is filled partially, and mixing occurs only at a free surface of the…

Condensed Matter · Physics 2009-10-30 S. N. Dorogovtsev

We present a multi-model simulation approach, targeted at understanding the behavior of comminution and the effect of grinding aids (GAs) in industrial cement mills. On the atomistic scale we use Molecular Dynamics (MD) simulations with…

One of the major shortcomings of discrete element modelling (DEM) is the computational cost required when the number of particles is huge, especially for fine powders and/or industry scale simulations. This study investigates the scaling of…

Soft Condensed Matter · Physics 2015-06-04 Subhash C. Thakur , Jin Y. Ooi , Hossein Ahmadian

Both discrete and continuum models have been widely used to study rapid granular flow, discrete model is accurate but computationally expensive, whereas continuum model is computationally efficient but its accuracy is doubtful in many…

Fluid Dynamics · Physics 2015-12-24 Xizhong Chen , Junwu Wang , Jinghai Li

We perform experiments and discrete element simulations on the dosing of cohesive granular materials in a simplified geometry. The setup is a simplified canister box where the powder is dosed out of the box through the action of a…

The paper develops a hybrid method for solving a system of advection--diffusion equations in a bulk domain coupled to advection--diffusion equations on an embedded surface. A monotone nonlinear finite volume method for equations posed in…

Computational Physics · Physics 2018-06-05 Alexey Y. Chernyshenko , Maxim A. Olshanskii , Yuri V. Vassilevski

We formulate a phenomenological model for the segregation of binary mixtures of rough and smooth granular materials in a rotating drum. Our model successfully replicates a range of experimental behaviours, e.g., rapid radial segregation;…

Condensed Matter · Physics 2007-05-23 Sanjay Puri , Hisao Hayakawa

Discrete element method simulations of confined bidisperse granular shear flows elucidate the balance between diffusion and segregation that can lead to either mixed or segregated states, depending on confining pressure. Results indicate…

Soft Condensed Matter · Physics 2018-09-24 Alexander M. Fry , Paul B. Umbanhowar , Julio M. Ottino , Richard M. Lueptow

A hydrogeological model for the spread of pollution in an aquifer is considered. The model consists in a convection-diffusion-reaction equation involving the dispersion tensor which depends nonlinearly of the fluid velocity. We introduce an…

Numerical Analysis · Mathematics 2020-06-05 Éloïse Comte

Discrete Element Method (DEM) simulations of granular media are computationally intensive, particularly during initialization phases dominated by large displacements and kinetic energy. This paper presents a novel generative pipeline based…

Machine Learning · Computer Science 2026-03-23 Muhammad Moeeze Hassan , Régis Cottereau , Filippo Gatti , Patryk Dec

The purpose of this work is to investigate the behavior of Multiscale Finite Element type methods for advection-diffusion problems in the advection-dominated regime. We present, study and compare various options to address the issue of the…

Numerical Analysis · Mathematics 2015-11-30 Claude Le Bris , Frederic Legoll , François Madiot

The discovery and study of new material systems rely on molecular simulations that often come with significant computational expense. We propose MDDM, a Molecular Dynamics Diffusion Model, which is capable of predicting a valid output…

Machine Learning · Computer Science 2025-09-11 Kevin Ferguson , Yu-hsuan Chen , Levent Burak Kara

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

Diffusion-based generative models (DBGMs) perturb data to a target noise distribution and reverse this process to generate samples. The choice of noising process, or inference diffusion process, affects both likelihoods and sample quality.…

Machine Learning · Computer Science 2023-03-06 Raghav Singhal , Mark Goldstein , Rajesh Ranganath