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Related papers: Enhancing semi-resolved CFD-DEM for dilute to dens…

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Coarse graining is an important ingredient in many multi-scale continuum-discrete solvers such as CFD--DEM (computational fluid dynamics--discrete element method) solvers for dense particle-laden flows. Although CFD--DEM solvers have become…

Computational Physics · Physics 2015-08-14 Rui Sun , Heng Xiao

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

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

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

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

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

An adpative integration technique for time advancement of particle motion in the context of coupled computational fluid dynamics (CFD) - discrete element method (DEM) simulations is presented in this work. CFD-DEM models provide an accurate…

Computational Physics · Physics 2018-02-28 Hariswaran Sitaraman , Ray Grout

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

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

Advancements in computing power have made it possible to numerically simulate large-scale fluid-mechanical and/or particulate systems, many of which are integral to core industrial processes. Among the different numerical methods available,…

Machine Learning · Computer Science 2025-02-28 Benedikt Alkin , Tobias Kronlachner , Samuele Papa , Stefan Pirker , Thomas Lichtenegger , Johannes Brandstetter

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

Sheared granular layers undergoing stick slip behavior are broadly employed to study the physics and dynamics of earthquakes. Here, a two dimensional implementation of the combined finite discrete element method (FDEM), which merges the…

The computational study of strongly-coupled, gas-solid flows at scales relevant to most environmental and engineering applications requires the use of `coarse-grained' methodologies such as the two-fluid model, particle-in-cell approach or…

Fluid Dynamics · Physics 2025-09-16 Lee Rosenberg , William Fullmer , Sarah Beetham

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

In this work, we present an alternative methodology to solve the particle-fluid interaction in the resolved CFDEM coupling framework. This numerical approach consists of coupling a Discrete Element Method (DEM) with a Computational Fluid…

Fluid Dynamics · Physics 2021-07-14 Ilberto Fonceca , Diego Maza , Raúl Cruz Hidalgo

Frictional instabilities in fluid saturated granular materials underlie natural hazards, including submarine landslides and earthquake initiation. Experiments show distinct failure behaviors under subaerial and subaqueous conditions due to…

Soft Condensed Matter · Physics 2025-12-25 Bimal Chhushyabaga , Behrooz Ferdowsi

Knowledge of the underlying mechanisms of multiphase flow dynamics in porous media is crucial for optimizing subsurface engineering applications like geological carbon sequestration. However, studying the micro-mechanisms of multiphase…

Fluid Dynamics · Physics 2025-08-01 Quanwei Dai , Kang Duan , Chung-Yee Kwok

A comparative study on mesh-based and mesh-less Computational Fluid Dynamics (CFD) approaches coupled with the Discrete Element Method (DEM) is presented. As the mesh-based CFD approach a Finite Volume Method (FVM) is used. A Smoothed…

Fluid Dynamics · Physics 2016-09-28 D. Markauskas , H. Kruggel-Emden , R. Sivanesapillai , H. Steeb

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale framework was proposed in this paper by applying a physics-guided data-driven approach. Instrumental to this framework, Feature Similarity…

Computational Physics · Physics 2019-10-18 Han Bao , Jinyong Feng , Nam Dinh , Hongbin Zhang

We present a computational framework for modeling large-scale particle-laden flows in complex domains with the goal of enabling simulations in medical-image derived patient specific geometries. The framework is based on a volume-filtered…

Fluid Dynamics · Physics 2023-11-28 Abhilash Reddy Malipeddi , C. Alberto Figueroa , Jesse Capecelatro
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