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We generalise the non-affine theory of viscoelasticity for use with large, well-sampled systems of arbitrary chemical complexity. Having in mind predictions of mechanical and vibrational properties of amorphous systems with atomistic…

Disordered Systems and Neural Networks · Physics 2020-07-27 Ivan Kriuchevskyi , Vladimir V. Palyulin , Rico Milkus , Robert M. Elder , Timothy W. Sirk , Alessio Zaccone

In this paper, we construct a combined multiscale finite element method (MsFEM) using the Local Orthogonal Decomposition (LOD) technique to solve the multiscale problems which may have singularities in some special portions of the…

Numerical Analysis · Mathematics 2022-09-14 Kuokuo Zhang , Weibing Deng , Haijun Wu

The sedimentation process of granular materials exists ubiquitously in nature and many fields which involve the solid-liquid separation. This paper employs the coupled computational fluid dynamics and discrete element method (CFD-DEM) to…

Fluid Dynamics · Physics 2017-11-07 Shan-Lin Xu , Rui Sun , Yuan-Qiang Cai , Hong-Lei Sun

We present a high-fidelity three dimensional computational framework for simulating the bulk mechanical behavior of granular aggregates composed of deformable brittle grains. Departing from classical discrete element methods (DEM), our…

Soft Condensed Matter · Physics 2025-07-16 Debdeep Bhattacharya , Davood Damircheli , Robert P. Lipton

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

We introduce the Fast Free Memory method (FFM), a new fast method for the numerical evaluation of convolution products. Inheriting from the Fast Multipole Method, the FFM is a descent-only and kernel-independent algorithm. We give the…

Numerical Analysis · Mathematics 2019-09-13 Matthieu Aussal , Marc Bakry

In this study, we propose a novel deep spatio-temporal point process model, Deep Kernel Mixture Point Processes (DKMPP), that incorporates multimodal covariate information. DKMPP is an enhanced version of Deep Mixture Point Processes…

Machine Learning · Computer Science 2023-10-10 Yixuan Zhang , Quyu Kong , Feng Zhou

We use the Discrete Element Method (DEM) to understand the underlying attenuation mechanism in granular media, with special applicability to the measurements of the so-called effective mass developed earlier. We consider that the particles…

Geophysics · Physics 2016-03-29 Yanqing Hu , Hernan A. Makse , John J. Valenza , David L. Johnson

We present a formalism for coupling a density functional theory-based quantum simulation to a classical simulation for the treatment of simple metallic systems. The formalism is applicable to multiscale simulations in which the part of the…

Materials Science · Physics 2009-11-10 Nicholas Choly , Gang Lu , Weinan E , Efthimios Kaxiras

We show that classical molecular density functional theory (MDFT), here in the homogeneous reference fluid approximation in which the functional is inferred from the properties of the bulk solvent, is a powerful new tool to study, at a…

A multi-scale model is presented for predicting the magnitude and rate of powder blending in a rotating drum blender. The model combines particle diffusion coefficient correlations from the literature with advective flow field information…

Soft Condensed Matter · Physics 2018-04-09 Yu Liu , Marcial Gonzalez , Carl Wassgren

We provide a numerical platform for the analysis of particle shape and topology effect on the macroscopic behavior of granular media. We work within a Discrete Element Method (DEM) framework and apply a peridynamic model for deformable…

Soft Condensed Matter · Physics 2023-08-09 Debdeep Bhattacharya , Robert P. Lipton

We study the effects of interatomic interactions on the quantum dynamics of a dense, nanoscale, atomic ensemble driven by a strong electromagnetic field. We use a self-consistent, mean-field technique based on the pseudo-spectral…

Quantum Physics · Physics 2018-01-17 C. S. DiLoreto , C. Rangan

The implementation of finite element methods (FEMs) for nonlocal models with a finite range of interaction poses challenges not faced in the partial differential equations (PDEs) setting. For example, one has to deal with weak forms…

Numerical Analysis · Mathematics 2020-05-22 Marta D'Elia , Max Gunzburger , Christian Vollmann

Discrete element (DEM) simulations demonstrate that granular materials are non-simple, meaning that the incremental stiffness of a granular assembly depends on the gradients of the strain increment as well as on the strain increment itself.…

Soft Condensed Matter · Physics 2018-12-20 Matthew R. Kuhn , Ching S. Chang

In two-component self-interacting dark matter (SIDM) models with inter-species interactions, mass segregation arises naturally from collisional relaxation, enhancing central densities and gravothermal evolution. We demonstrate that models…

Cosmology and Nongalactic Astrophysics · Physics 2026-04-08 Daneng Yang , Yi-Zhong Fan , Siyuan Hou , Yue-Lin Sming Tsai

The packing behavior of powders is significantly influenced by various types of inter-particle attractive forces, including adhesion and non-bonded van der Waals forces [1, 2, 3, 4, 5, 6]. Alongside particle size and shape distributions,…

The use of molecular dynamics (MD) simulations has led to promising results to unravel the atomistic origins of adhesive wear, and in particular for the onset of wear at nanoscale surface asperities. However, MD simulations come with a high…

Soft Condensed Matter · Physics 2022-06-29 Son Pham-Ba , Jean-François Molinari

Computational prediction of enzyme mechanism and protein function requires accurate physics-based models and suitable sampling. We discuss recent advances in large-scale quantum mechanical (QM) modeling of biochemical systems that have…

Chemical Physics · Physics 2021-05-28 Vyshnavi Vennelakanti , Azadeh Nazemi , Rimsha Mehmood , Adam H. Steeves , Heather J. Kulik

We introduce the multivariate decomposition finite element method (MDFEM) for solving elliptic PDEs with uniform random diffusion coefficients. We show that the MDFEM can be used to reduce the computational complexity of estimating the…

Numerical Analysis · Mathematics 2021-07-28 Dong T. P. Nguyen , Dirk Nuyens