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相关论文: An efficient method for particle-resolved simulati…

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A novel smooth immersed boundary method (IBM) based on a direct-forcing formulation is proposed to simulate incompressible dense particle-laden flows. This IBM relies on a regularization of the transfer function between the Eulerian grid…

计算物理 · 物理学 2023-04-24 Victor Chéron , Fabien Evrard , Berend van Wachem

The Immersed Boundary Method (IBM) is one of the popular one-fluid mixed Eulerian-Lagrangian methods to simulate motion of droplets. While the treatment of a moving complex boundary is an extremely time consuming and formidable task in a…

计算物理 · 物理学 2018-07-30 Chia Rui Ong , Hiroaki Miura

In the present paper, a fluid-particle coupling method is directly derived from the Navier-Stokes equations (NSE) by applying the concept of volume-filtering, yielding a physically consistent methodology to incorporate solid wall boundary…

流体动力学 · 物理学 2024-10-17 Max Hausmann , Hani Elmestikawy , Berend van Wachem

A boundary thickening-based direct forcing (BTDF) immersed boundary (IB) method is proposed for fully resolved simulation of incompressible viscous flows laden with finite size particles. By slightly thickening the boundary thickness, the…

计算物理 · 物理学 2020-06-26 Maoqiang Jiang , Zhaohui Liu

We present an improved method for computing incompressible viscous flow around suspended rigid particles using a fixed and uniform computational grid. The main idea is to incorporate Peskin's regularized delta function approach [Acta…

流体动力学 · 物理学 2018-09-24 Markus Uhlmann

The immersed boundary lattice Boltzmann method (IB-LBM) has been widely used in the simulation of fluid-solid interaction and particulate flow problems, since proposed in 2004. However, it is usually a non-trivial task to retain the…

计算物理 · 物理学 2018-03-28 Shi Tao , Qing He , Baiman Chen , Simin Huang

In this paper, the Immersed Boundary Method (IBM) proposed by Pinelli is implemented for finite volume approximations of incompressible Navier-Stokes equations solutions in the open source toolbox OpenFOAM version 2.2. Solid obstacles are…

流体动力学 · 物理学 2016-09-15 E. Constant , C. Li , J. Favier , M. Meldi , P. Meliga , E. Serre

The present work extends the direct-forcing immersed boundary method introduced by Garc\'ia-Villalba et al. (2023), broadening its application from spherical to arbitrarily-shaped particles, while maintaining its capacity to address both…

流体动力学 · 物理学 2025-04-18 Maximilian Schenk , Manuel García-Villalba , Jan Dušek , Markus Uhlmann , Manuel Moriche

It is well known that the number of particles should be scaled up to enable industrial scale simulation. The calculations are more computationally intensive when the motion of the surrounding fluid is considered. Besides the advances in…

计算物理 · 物理学 2014-07-28 Hao Zhang , F. Xavier Trias , Assensi Oliva , Dongmin Yang , Yuanqiang Tan , Shi Shu , Yong Sheng

We present a collocated-grid framework for Direct Numerical Simulations of polydisperse particles submerged in a viscous fluid. The fluid-particle forces are coupled with the Immersed Boundary Method (IBM) while the particle-particle forces…

The direct-forcing immersed boundary method (DF-IBM) algorithm previously developed by the authors is extended by coupling the Navier-Stokes equations with the Newton-Euler equations for rigid body dynamics within the DF-IBM framework. This…

流体动力学 · 物理学 2026-04-28 E. Farah , A. Ouahsine , P. G. Verdin , B. Kaoui

Fully resolved simulation of flows with buoyant particles is a challenging problem since buoyant particles are lighter than the surrounding fluid, and as a result, the two phases are strongly coupled together. In this work, the virtual…

流体动力学 · 物理学 2020-08-05 Vahid Tavanashad , Shankar Subramaniam

In our recent work [H. Zhang, F.X. Trias, A. Oliva, D. Yang, Y. Tan, Y. Sheng. PIBM: Particulate immersed boundary method for fluid-particle interaction problems. Powder Technology. 272(2015), 1-13.], a particulate immersed boundary method…

计算物理 · 物理学 2015-02-05 Hao Zhang , Haizhuan Yuan , F. Xavier Trias , Aibing Yu , Yuanqiang Tan , Assensi Oliva

In the present study, a discrete forcing Immersed Boundary Method (IBM) is proposed for the numerical simulation of high-speed flow problems including heat exchange. The flow field is governed by the compressible Navier-Stokes equations,…

流体动力学 · 物理学 2023-01-24 Hamza Riahi , Eric Goncalves , Marcello Meldi

The immersed boundary-finite element method (IBFE) is an approach to describing the dynamics of an elastic structure immersed in an incompressible viscous fluid. In this formulation, there are discontinuities in the pressure and viscous…

数值分析 · 数学 2020-03-18 Charles Puelz , Boyce E. Griffith

In this work, the Immersed Boundary Method (IBM) with feedback forcing introduced by Goldstein et al. (1993) and often referred in the literature as the Virtual Boundary Method (VBM), is addressed. The VBM has been extensively applied both…

数值分析 · 数学 2021-10-25 Michele Girfoglio , Giovanni Stabile , Andrea Mola , Gianluigi Rozza

Detailed data describing the motion of a rigid sphere settling in unperturbed fluid is generated by means of highly-accurate spectral/spectral-element simulations with the purpose of serving as a future benchmark case. A single…

流体动力学 · 物理学 2013-11-26 Markus Uhlmann , Jan Dusek

This paper presents an improved immersed moving boundary model (IBM) for solving complex fluid-particle interactions in a coupled lattice Boltzmann method (LBM) and an adhesive discrete element method (DEM), using the "partially saturated…

软凝聚态物质 · 物理学 2020-10-21 Wenwei Liu , Chuan-Yu Wu

The Immersed Boundary (IB) method is a mathematical framework for constructing robust numerical methods to study fluid-structure interaction in problems involving an elastic structure immersed in a viscous fluid. The IB formulation uses an…

A discrete unified gas kinetic scheme (DUGKS) coupled with the immersed boundary (IB) method is developed to perform interface-resolved simulation of particle-laden flows. The present method (IB-DUGKS) preserves the respective advantages of…

流体动力学 · 物理学 2018-10-17 Shi Tao , Haolong Zhang , Zhaoli Guo , Lian-Ping Wang
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