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In this work, a coarse-graining method previously proposed by the authors in a companion paper based on solving diffusion equations is applied to CFD-DEM simulations, where coarse graining is used to obtain solid volume fraction, particle…

Computational Physics · Physics 2015-01-07 Rui Sun , Heng Xiao

Computational fluid dynamics and discrete element method (CFD-DEM) coupling is an efficient and powerful tool to simulate particle-fluid systems. However, current volume-averaged CFD-DEM relying on direct grid-based mapping between the…

Fluid Dynamics · Physics 2025-06-12 Yuxiang Liu , Lu Jing , Xudong Fu , Huabin Shi

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

Sand production is an important issue for many hydrocarbon recovery applications in unconsolidated reservoirs. The model using the Computational Fluid Dynamics coupled with Discrete Element Method (CFD-DEM) can capture micro-scale features…

Computational Engineering, Finance, and Science · Computer Science 2022-11-14 Daniyar Kazidenov , Furkhat Khamitov , Yerlan Amanbek

Development of algorithms and growth of computational resources in the past decades have enabled simulations of sediment transport processes with unprecedented fidelities. The Computational Fluid Dynamics--Discrete Element Method (CFD--DEM)…

Computational Physics · Physics 2017-09-13 Rui Sun , Heng Xiao

To acquire the ability to numerically study the rheology of particulate two-phase flows that lack scale separation, we present a general method to average or coarse-grain the equations of motion of a mixture of a continuous fluid of…

Fluid Dynamics · Physics 2026-01-22 Thomas Pähtz , Yulan Chen , Rui Zhu , Katharina Tholen , Zhiguo He

In unresolved flow CFD-DEM simulations, the porosity values for each CFD cell are determined using a coarse-graining algorithm. While this approach enables coupled simulations of representative numbers of particles, the influence of the…

Fluid Dynamics · Physics 2022-04-18 Hanqiao Che , Catherine O'Sullivan , Adnan Sufian , Edward Smith

The gradient discretisation method (GDM) is a generic framework for designing and analysing numerical schemes for diffusion models. In this paper, we study the GDM for the porous medium equation, including fast diffusion and slow diffusion…

Numerical Analysis · Mathematics 2020-04-02 Jerome Droniou , Kim-Ngan Le

Many dense granular systems are non-monodisperse, consisting of particles of different sizes, and will segregate based on size during flow. This phenomenon is an important aspect of many industrial and geophysical processes, necessitating…

Soft Condensed Matter · Physics 2024-05-28 Harkirat Singh , David L. Henann

We present a real-space formulation for coarse-graining Kohn-Sham Density Functional Theory that significantly speeds up the analysis of material defects without appreciable loss of accuracy. The approximation scheme consists of two steps.…

Computational Physics · Physics 2015-06-11 Phanish Suryanarayana , Kaushik Bhattacharya , Michael Ortiz

The first paper of this series [J. Chem. Phys. 158, 034103 (2023)] demonstrated that excess entropy scaling holds for both fine-grained and corresponding coarse-grained (CG) systems. Despite its universality, a more exact determination of…

Chemical Physics · Physics 2023-01-18 Jaehyeok Jin , Kenneth S. Schweizer , Gregory A. Voth

We present the conceptual and technical background required to describe and understand the correlations and fluctuations of the empirical density and current of steady-state diffusion processes on all time scales -- observables central to…

Statistical Mechanics · Physics 2023-04-06 Cai Dieball , Aljaž Godec

CFD-DEM is used to simulate solid-fluid systems. DEM models the motion of discrete particles while CFD models the fluid phase. Coupling both necessitates the calculation of the void fraction and the solid-fluid forces resulting in a…

Fluid Dynamics · Physics 2023-01-06 Toni El Geitani , Shahab Golshan , Bruno Blais

In this study, a coarse-graining framework for discrete models is formulated on the basis of multiscale homogenization. The discrete model considered in this paper is the Lattice Discrete Particle Model (LDPM), which simulates concrete at…

Materials Science · Physics 2018-04-24 Erol Lale , Roozbeh Rezakhani , Mohammed Alnaggar , Gianluca Cusatis

We present a multiscale simulation algorithm for amorphous materials, which we illustrate and validate in a canonical case of dense granular flow. Our algorithm is based on the recently proposed Spot Model, where particles in a dense random…

Soft Condensed Matter · Physics 2009-11-11 Chris H. Rycroft , Martin Z. Bazant , Gary S. Grest , James W. Landry

We present a coarse-graining strategy for reducing the number of particle species in mixtures to achieve a simpler system with higher diffusion while preserving the total particle number and characteristic dynamic features. As a system of…

Soft Condensed Matter · Physics 2020-09-16 Thomas Heinemann , YounJoon Jung

An expression for the stress tensor near an external boundary of a discrete mechanical system is derived explicitly in terms of the constituents' degrees of freedom and interaction forces. Starting point is the exact and general coarse…

Soft Condensed Matter · Physics 2011-08-26 Thomas Weinhart , Anthony R. Thornton , Stefan Luding , Onno Bokhove

Computational fluid dynamics (CFD) is a powerful tool for modeling turbulent flow and is commonly used for urban microclimate simulations. However, traditional CFD methods are computationally intensive, requiring substantial hardware…

In the present article, novel Coarse-Graining (CG) algorithms for the Eulerian-Lagrangian (EL) simulation of particle-laden flows are proposed. These include different variants of Reproducing Kernel Particle Methods (RKPM) and an extended…

Fluid Dynamics · Physics 2025-11-12 H. Eshraghi , E. Amani , M. Saffar-Avval

Diffusion models (DMs) have been adopted across diverse fields with its remarkable abilities in capturing intricate data distributions. In this paper, we propose a Fast Diffusion Model (FDM) to significantly speed up DMs from a stochastic…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Zike Wu , Pan Zhou , Kenji Kawaguchi , Hanwang Zhang
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