English
Related papers

Related papers: Multiscale simulation of rarefied polyatomic gas f…

200 papers

To simulate the dynamics of fluid with polydisperse particles on macroscale level, one has to solve hydrodynamic equations with several relaxation terms, representing momentum transfer from fluid to particles and vice versa. For small…

Cellular scale decision making is modulated by the dynamics of signalling molecules and their diffusive trajectories from a source to small absorbing sites on the cellular surface. Diffusive capture problems are computationally challenging…

Numerical Analysis · Mathematics 2025-07-16 Alan E. Lindsay , Andrew J. Bernoff

We develop an efficient parallel multiscale method that bridges the atomistic and mesoscale regimes, from nanometer to micron and beyond, via concurrent coupling of atomistic simulation and mesoscopic dynamics. In particular, we combine an…

Computational Physics · Physics 2020-12-23 Yuying Wang , Zhen Li , Junbo Xu , Chao Yang , George Em Karniadakis

In the context of the validation of PICLas, a kinetic particle suite for the simulation of rarefied, non-equilibrium plasma flows, the biased hypersonic nitrogen flow around a blunted cone was simulated with the Direct Simulation Monte…

Computational Physics · Physics 2018-11-13 T. Binder , S. Copplestone , A. Mirza , P. Nizenkov , P. Ortwein , M. Pfeiffer , W. Reschke , C. -D. Munz , S. Fasoulas

We present a simulation scheme for discrete-velocity gases based on {\em local thermodynamic equilibrium}. Exploiting the kinetic nature of discrete-velocity gases, in that context, results in a natural splitting of fluxes, and the…

comp-gas · Physics 2008-02-03 Balu Nadiga , Dale Pullin

Most of numerical methods for deterministic simulations of rarefied gas flows use the discrete velocity (or discrete ordinate) approximation. In this approach, the kinetic equation is approximated with a global velocity grid. The grid must…

Numerical Analysis · Mathematics 2014-03-19 Stéphane Brull , Luc Mieussens

The parallel solver of the general synthetic iterative scheme (GSIS), as recently developed by Zhang \textit{et. al.} in Comput. Fluids 281 (2024) 106374, is an efficient method to find the solution of the Boltzmann equation…

Computational Physics · Physics 2025-01-07 Yanbing Zhang , Jianan Zeng , Lei Wu

The numerically exact path integral Monte Carlo approach for the real-time evolution of dissipative quantum systems (PIMC), particularly suited for systems with discrete configuration space (tight-binding systems), is extended to treat…

Statistical Mechanics · Physics 2009-11-11 Lothar Muehlbacher , Charlotte Escher , Joachim Ankerhold

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

In rarefied gas flows, the spatial grid size could vary by several orders of magnitude in a single flow configuration (e.g., inside the Knudsen layer it is at the order of mean free path of gas molecules, while in the bulk region it is at a…

Fluid Dynamics · Physics 2021-04-02 Lei Wu

The Dynamical Graph Grammar (DGG) formalism can describe complex system dynamics with graphs that are mapped into a master equation. An exact stochastic simulation algorithm may be used, but it is slow for large systems. To overcome this…

Quantitative Methods · Quantitative Biology 2024-07-16 Eric Medwedeff , Eric Mjolsness

We introduce a simplified technique for incorporating diffusive phenomena into lattice-gas molecular dynamics models. In this method, spatial interactions take place one dimension at a time, with a separate fractional timestep devoted to…

Cellular Automata and Lattice Gases · Physics 2007-05-23 Raissa M. D'Souza , Norman H. Margolus , Mark A. Smith

Particle Markov Chain Monte Carlo methods are used to carry out inference in non-linear and non-Gaussian state space models, where the posterior density of the states is approximated using particles. Current approaches usually perform…

Computation · Statistics 2019-09-30 Eduardo F. Mendes , Christopher K. Carter , David Gunawan , Robert Kohn

We propose a modification, based on the RESTART (repetitive simulation trials after reaching thresholds) and DPR (dynamics probability redistribution) rare event simulation algorithms, of the standard diffusion Monte Carlo (DMC) algorithm.…

Probability · Mathematics 2014-04-10 Martin Hairer , Jonathan Weare

In this paper, we propose a robust and efficient numerical framework for simulating multicomponent gas flow in poroelastic media, with a focus on preserving fundamental thermodynamic principles and ensuring computational reliability. The…

Numerical Analysis · Mathematics 2026-03-03 Huangxin Chen , Yuxiang Chen , Jisheng Kou , Shuyu Sun

A kinetic model is proposed for rarefied flows of molecular gas with rotational and temperature-dependent vibrational degrees of freedom. The model reduces to the Boltzmann equation for monatomic gas when the energy exchange between the…

Fluid Dynamics · Physics 2022-01-19 Qi Li , Lei Wu

We propose a method for efficiently coupling the finite element method with atomistic simulations, while using molecular dynamics or kinetic Monte Carlo techniques. Our method can dynamically build an optimized unstructured mesh that…

Computational Engineering, Finance, and Science · Computer Science 2018-05-23 Mihkel Veske , Andreas Kyritsakis , Kristjan Eimre , Vahur Zadin , Alvo Aabloo , Flyura Djurabekova

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

Molecular dynamics (MD) simulation is essential for various scientific domains but computationally expensive. Learning-based force fields have made significant progress in accelerating ab-initio MD simulation but are not fast enough for…

Machine Learning · Computer Science 2023-08-29 Xiang Fu , Tian Xie , Nathan J. Rebello , Bradley D. Olsen , Tommi Jaakkola

Efficient analysis and simulation of multiscale stochastic systems of chemical kinetics is an ongoing area for research, and is the source of many theoretical and computational challenges. In this paper, we present a significant improvement…

Numerical Analysis · Mathematics 2016-09-21 Simon Cotter