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The design of microfluidic devices is a cumbersome and tedious process that can be significantly improved by simulation. Methods based on Computational Fluid Dynamics (CFD) are considered state-of-the-art, but require extensive compute time…

Computational Engineering, Finance, and Science · Computer Science 2024-01-17 Michel Takken , Robert Wille

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}…

Computational Physics · Physics 2026-02-26 Ehsan Roohi , Ahmad Shoja-Sani , Stefan Stefanov

A grid-free variant of the Direct Simulation Monte Carlo (DSMC) method is proposed, named the Isotropic DSMC (I-DSMC) method, that is suitable for simulating dense fluid flows at molecular scales. The I-DSMC algorithm eliminates all grid…

Statistical Mechanics · Physics 2015-05-13 A. Donev , B. J. Alder , A. L. Garcia

We propose a method for multi-scale hybrid simulations of molecular dynamics (MD) and computational fluid dynamics (CFD). In the method, usual lattice-mesh based simulations are applied for CFD level, but each lattice is associated with a…

Soft Condensed Matter · Physics 2014-01-20 Shugo Yasuda , Ryoichi Yamamoto

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…

Astrophysics · Physics 2007-05-23 Takuya Matsuda , Hiromi Mizutani , Henri M. J. Boffin

The Dynamic Monte Carlo (DMC) method is an established molecular simulation technique for the analysis of the dynamics in colloidal suspensions. An excellent alternative to Brownian Dynamics or Molecular Dynamics simulation, DMC is…

Soft Condensed Matter · Physics 2020-07-15 Fabián A. García Daza , Alejandro Cuetos , Alessandro Patti

The low-variance direct simulation Monte Carlo (LVDSMC) is a powerful method to simulate low-speed rarefied gas flows. However, in the near-continuum flow regime, due to limitations on the time step and spatial cell size, it takes plenty of…

Fluid Dynamics · Physics 2022-10-18 Liyan Luo , Qi Li , Lei Wu

A computational fluid dynamics (CFD) simulation framework for fluid-flow prediction is developed on the Tensor Processing Unit (TPU) platform. The TPU architecture is featured with accelerated dense matrix multiplication, large high…

Computational Physics · Physics 2022-03-02 Qing Wang , Matthias Ihme , Yi-Fan Chen , John Anderson

This paper introduces open-source computational fluid dynamics software named open computational fluid dynamic code for scientific computation with graphics processing unit (GPU) system (OpenCFD-SCU), developed by the authors for direct…

Fluid Dynamics · Physics 2022-12-21 Guanlin Dang , Shiwei Liu , Tongbiao Guo , Junyi Duan , Xinliang Li

In the present work, we present a novel numerical algorithm to couple the Direct Simulation Monte Carlo method (DSMC) for the solution of the Boltzmann equation with a finite volume like method for the solution of the Euler equations.…

Numerical Analysis · Mathematics 2014-04-08 Pierre Degond , Giacomo Dimarco

An accurate algorithm is proposed to improve the prediction of a particle in collision with a moving wall within the direct simulation Monte Carlo (DSMC) framework for the simulation of unsteady rarefied flows. This algorithm is able to…

Computational Physics · Physics 2021-09-29 He Zhang , Fanli Shan , Hong Fang , Xing Zhang , Jun Zhang , Jinghua Sun

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…

The present study employs the Direct Simulation Monte Carlo (DSMC) method, a widely used numerical method for studying non-continuum flows, to investigate the flow characteristics of a chemically reacting hypersonic flow over a…

Fluid Dynamics · Physics 2021-12-01 Arjun Singh

We develop an online optimisation algorithm for in situ calibration of collision models in simulations of rarefied gas flows. The online optimised collision models are able to achieve similar accuracy to Direct Molecular Simulation (DMS) at…

Fluid Dynamics · Physics 2024-11-21 Nicholas Daultry Ball , Jonathan F. MacArt , Justin Sirignano

Turbulent flow has been extensively studied using computational fluid dynamics (CFD) simulations since turbulent flow regime is so frequently encountered in both academic and engineering applications. The high-fidelity simulation of the…

Fluid Dynamics · Physics 2024-05-21 Minghan Chu

Computer simulation is an important tool for scientific progress, especially when lab experiments are either extremely costly and difficult or lack the required resolution. However, all of the simulation methods come with limitations. In…

Fluid Dynamics · Physics 2023-08-04 Edward R. Smith , Panagiotis E. Theodorakis

The Direct Simulation Monte Carlo (DSMC) method remains the gold standard for simulating rarefied gas flows but is prohibitively expensive for parametric and many-query applications. To address this limitation, we introduce a Deep Operator…

Fluid Dynamics · Physics 2025-09-23 Ehsan Roohi , Amirmehran Mahdavi

The gas-kinetic scheme (GKS) provides high computational efficiency and accuracy for continuum flow simulations but is unable to reliably capture rarefaction effects. In contrast, although the discrete velocity method (DVM) is better suited…

Fluid Dynamics · Physics 2026-05-08 Hangkong Wu , Yuze Zhu , Yajun Zhu , Kun Xu

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…

Numerical Analysis · Mathematics 2025-09-05 Thijs Steel , Vince Maes , Giovanni Samaey

Transient computational fluid dynamics (CFD) simulations are essential for many industrial applications, but suffer from high compute costs relative to steady-state simulations. This is due to the need to: (a) reach statistical steadiness…

Machine Learning · Computer Science 2025-06-16 Peter Sharpe , Rishikesh Ranade , Kaustubh Tangsali , Mohammad Amin Nabian , Ram Cherukuri , Sanjay Choudhry