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We present a lattice-gas (generalised Ising) model for liquid droplets on solid surfaces. The time evolution in the model involves two processes: (i) Single-particle moves which are determined by a kinetic Monte Carlo algorithm. These…

Soft Condensed Matter · Physics 2019-11-06 Mounirah Areshi , Dmitri Tseluiko , Andrew J. Archer

We construct a rejection-free Monte Carlo method for the hard-disk system. Rejection-free Monte Carlo methods preserve the time-evolution behavior of the standard Monte Carlo method, and this relationship is confirmed for our method by…

Statistical Mechanics · Physics 2015-06-24 H. Watanabe , S. Yukawa , M. A. Novotny , N. Ito

This paper presents a novel method for smoothed particle hydrodynamics (SPH) with thin-walled structures. Inspired by the direct forcing immersed boundary method, this method employs a moving least square method to guarantee the smoothness…

Fluid Dynamics · Physics 2023-10-10 ZhuoLin Wang , Zichao Jiang , Yi Zhang , Gengchao Yang , Trevor Hocksun Kwan , Yuhui Chen , Qinghe Yao

We show that the common local Monte Carlo rules used to simulate the motion of driven flux lines in disordered media cannot capture the interplay between elasticity and disorder which lies at the heart of these systems. We therefore discuss…

Disordered Systems and Neural Networks · Physics 2009-11-07 Alberto Rosso , Werner Krauth

A new approach to simulation of stationary flows by Direct Simulation Monte Carlo method is proposed. The idea is to specify an individual time step for each component of a gas mixture. The approach consists of modifications mainly to…

Computational Physics · Physics 2016-08-24 Roman V. Maltsev

We develop a diffuse solid method that is versatile and accurate for modeling wetting and multiphase flows in highly complex geometries. In this scheme, we harness N + 1-component phase field models to investigate interface shapes and flow…

Flow control is of interest in many open and wall-bounded shear flows in order to reduce drag or to avoid sudden large fluctuations that may lead to material failure. An established means of control is the application of suction through a…

Fluid Dynamics · Physics 2020-02-10 Moritz Linkmann , Bruno Eckhardt

Optical turbulence modelling and simulation are crucial for developing astronomical ground-based instruments, laser communication, laser metrology, or any application where light propagates through a turbulent medium. In the context of…

Instrumentation and Methods for Astrophysics · Physics 2024-04-05 A. Berdja , M. Hadjara , M. Carbillet , R. L. Bernardi , R. G. Petrov

A method of random forcing with a constant power input for two-dimensional gyrokinetic turbulence simulations is developed for the study of stationary plasma turbulence. The property that the forcing term injects the energy at a constant…

Plasma Physics · Physics 2021-03-29 Ryusuke Numata

In parallelized Monte-Carlo simulations, the order of summation is not always the same. When the mean is calculated in running fashion, this may create an artificial randomness in results which ought to be reproducible. This note takes a…

Computational Finance · Quantitative Finance 2022-09-13 Jherek Healy

Realistic fluid-solid interaction potentials are essential in description of confined fluids especially in the case of geometric heterogeneous surfaces. Correlated random field is considered as a model of random surface with high geometric…

Statistical Mechanics · Physics 2017-05-24 Aleksey Khlyupin , Timur Aslyamov

Modeling of wall-bounded turbulent flows is still an open problem in classical physics, with only modest progress made in the last few decades beyond the so-called `log law', which describes only the intermediate region in wall-bounded…

Fluid Dynamics · Physics 2018-08-31 Fangying Song , George Em Karniadakis

By the Wolff's cluster Monte Carlo simulations and numerical minimization within a mean field approach, we study the low temperature phase diagram of water, adopting a cell model that reproduces the known properties of water in its fluid…

Soft Condensed Matter · Physics 2009-11-13 Marco G. Mazza , Kevin Stokely , Elena Strekalova , H. Eugene Stanley , Giancarlo Franzese

Context. A universally accepted definition of what a vortex is has not yet been reached. Therefore, we lack an unambiguous and rigorous method for the identification of vortices in fluid flows. Such a method would be necessary to conduct…

Solar and Stellar Astrophysics · Physics 2022-12-14 José Roberto Canivete Cuissa , Oskar Steiner

We have developed a novel Monte Carlo method for simulating the dynamical evolution of stellar systems in arbitrary geometry. The orbits of stars are followed in a smooth potential represented by a basis-set expansion and perturbed after…

Astrophysics of Galaxies · Physics 2014-12-04 Eugene Vasiliev

Separated flows past complex geometries are modelled by discrete vortex techniques. The flows are assumed to be rotational and inviscid, and a new technique is described to determine the streamfunctions for linear shear profiles. The…

chao-dyn · Physics 2007-05-23 P. Franzese , L. Zannetti

The aim of this paper is to introduce a new Monte Carlo method based on importance sampling techniques for the simulation of stochastic differential equations. The main idea is to combine random walk on squares or rectangles methods with…

Probability · Mathematics 2010-10-22 Madalina Deaconu , Antoine Lejay

We study all the possibilities of producing rotating flow in an incompressible fluid by electric and magnetic fields. We start with a general theoretical basis and look for different configurations and set-ups which electric/magnetic field…

Fluid Dynamics · Physics 2013-03-25 A. Amjadi , A. Nejati , S. O. Sobhani , R. Shirsavar

While boundary plasmas in present-day tokamaks generally fall in a fluid regime, neutral species near the boundary often require kinetic models due to long mean-free-paths compared to characteristic spatial scales in the region. Monte-Carlo…

Plasma Physics · Physics 2025-01-31 Gregory J. Parker , Maxim V. Umansky , Benjamin D. Dudson

Markov chain Monte Carlo is a widely-used technique for generating a dependent sequence of samples from complex distributions. Conventionally, these methods require a source of independent random variates. Most implementations use…

Computation · Statistics 2012-04-17 Iain Murray , Lloyd T. Elliott