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The Direct Simulation Monte Carlo (DSMC) method is widely employed for simulating rarefied nonequilibrium gas flows. With advances in aerospace engineering and micro/nano-scale technologies, gas flows exhibit the coexistence of rarefied and…

计算物理 · 物理学 2025-07-01 Hao Jin , Sha Liu , Sirui Yang , Junzhe Cao , Congshan Zhuo , Chengwen Zhong

The influence and validity of wall boundary conditions for non-equilibrium fluid flows described by the Boltzmann equation remains an open problem. The substantial computational cost of directly solving the Boltzmann equation has limited…

流体动力学 · 物理学 2024-01-02 Tarik Dzanic , Freddie D. Witherden , Luigi Martinelli

The Direct Simulation Monte Carlo (DSMC) method is the gold standard for non-equilibrium rarefied gas dynamics, yet its computational cost can be prohibitive, especially for near-continuum regimes and high-fidelity \emph{ab initio}…

计算物理 · 物理学 2026-02-26 Ehsan Roohi , Ahmad Shoja-Sani , Stefan Stefanov

First of all, this paper presents some improvements of DSMC method in the form of new schemes and approaches, that, for a wide class of problems, increase performance and reduce the demands on computer resources. The most important…

流体动力学 · 物理学 2012-01-16 Roman V. Maltsev

We describe collective-move Monte Carlo algorithms designed to approximate the overdamped dynamics of self-assembling nanoscale components equipped with strong, short-ranged and anisotropic interactions. Conventional Monte Carlo simulations…

统计力学 · 物理学 2012-04-16 Stephen Whitelam

A fundamental step in the rational design of vascular targeted particles is the firm adhesion at the blood vessel walls. Here, a combined Lattice Boltzmann Immersed Boundary model is presented for predicting the near wall dynamics of…

流体动力学 · 物理学 2018-08-07 A. Coclite , H. Mollica , S. Ranaldo , G. Pascazio , M. D. De Tullio , P. Decuzzi

In plasma edge simulations, kinetic Monte Carlo (MC) is often used to simulate neutral particles and estimate source terms. For large-sized reactors, like ITER and DEMO, high particle collision rates lead to a substantial computational cost…

计算工程、金融与科学 · 计算机科学 2025-09-16 Zhirui Tang , Emil Løvbak , Julian Koellermeier , Giovanni Samaey

The accuracy of Euler-Lagrange point-particle models employed in particle-laden fluid flow simulations depends on accurate estimation of the particle force through closure models. Typical force closure models require computation of the slip…

流体动力学 · 物理学 2020-04-14 Pedram Pakseresht , Mahdi Esmaily , Sourabh V. Apte

The behavior of a Lattice Monte Carlo algorithm (if it is designed correctly) must approach that of the continuum system that it is designed to simulate as the time step and the mesh step tend to zero. However, we show for an algorithm for…

统计力学 · 物理学 2010-08-23 Mykyta V. Chubynsky , Gary W. Slater

We introduce a `virtual-move' Monte Carlo (VMMC) algorithm for systems of pairwise-interacting particles. This algorithm facilitates the simulation of particles possessing attractions of short range and arbitrary strength and geometry, an…

统计力学 · 物理学 2009-11-11 Stephen Whitelam , Phillip L. Geissler

We consider non-spherical rigid body particles in an incompressible fluid in the regime where the particles are too large to assume that they are simply transported with the fluid without back-coupling and where the particles are also too…

流体动力学 · 物理学 2021-09-07 Henry von Wahl , Thomas Richter

Computational fluid dynamics (CFD) is increasingly used to study blood flows in patient-specific arteries for understanding certain cardiovascular diseases. The techniques work quite well for relatively simple problems, but need…

计算物理 · 物理学 2018-10-11 Fande Kong , Vitaly Kheyfets , Ender Finol , Xiao-Chuan Cai

We apply the Direct Simulation Monte Carlo (DSMC) method, developed originally to calculate rarefied gas dynamical problems, to study the gas flow in an accretion disc in a close binary system. The method involves viscosity and thermal…

天体物理学 · 物理学 2007-05-23 Takuya Matsuda , Hiromi Mizutani , Henri M. J. Boffin

Kinetic equations model the position-velocity distribution of particles subject to transport and collision effects. Under a diffusive scaling, these combined effects converge to a diffusion equation for the position density in the limit of…

数值分析 · 数学 2023-07-26 Emil Løvbak , Giovanni Samaey

A common feature of wall-bounded turbulent particle-laden flows is enhanced particle concentrations in a thin layer near the wall due to a phenomenon known as turbophoresis. Even at relatively low bulk volume fractions, particle-particle…

流体动力学 · 物理学 2019-08-09 Perry L. Johnson

The Kinetic-Diffusion Monte Carlo (KDMC) method is a powerful tool for simulating neutral particles in fusion reactors. It is a hybrid fluid-kinetic method that is significantly faster than pure kinetic methods at the cost of a small bias…

数值分析 · 数学 2025-09-05 Thijs Steel , Vince Maes , Giovanni Samaey

Functional integral representations for solutions of the motion equations for wall-bounded incompressible viscous flows, expressed (implicitly) in terms of distributions of solutions to stochastic differential equations of McKean-Vlasov…

数值分析 · 数学 2024-03-26 Vladislav Cherepanov , Sebastian W. Ertel , Zhongmin Qian , Jiang-Lun Wu

In this paper, we propose an approach for simulating wall-bounded incompressible turbulent flows by integrating the technology of random vortex method with the core principles of large-eddy simulations (LES). In particular, we employ the…

流体动力学 · 物理学 2025-11-11 Zihao Guo , Zhongmin Qian

In plasma edge simulations, the behavior of neutral particles is often described by a Boltzmann--BGK equation. Solving this kinetic equation and estimating the moments of its solution are essential tasks, typically carried out using Monte…

数值分析 · 数学 2025-12-30 Zhirui Tang , Julian Koellermeier , Emil Løvbak , Giovanni Samaey

A novel multiscale numerical method is developed to accelerate direct simulation Monte Carlo (DSMC) simulations for polyatomic gases with internal energy. This approach applies the general synthetic iterative scheme to stochastic…

计算物理 · 物理学 2025-01-22 Liyan Luo , Tao Huang , Qi Li , Lei Wu
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