This article discusses some numerical pitfalls associated with the classical solution of stochastic Langevin equations via the Euler–Langevin algorithm for long-term dispersion features. A simple operator-splitting algorithm is proposed to overcome these short-comings and, starting from it, a simple and computationally consistent algorithm for the simulation of stochastic differential equations is presented. Dispersion properties of tracer particles in cylindrical wavy channels and cellular flows are addressed in detail. Numerical results of the two algorithms proposed are compared with numerical results obtained from Brenner’s macrotransport theory
Kinetic Monte Carlo methods provide a powerful computational tool for the simulation of microscopic ...
A stochastic algorithm based on the Langevin equation has been recently proposed to simulate rarefie...
This paper introduces time-continuous numerical schemes to simulate stochastic differential equation...
The aim of this talk is the analysis of the long-term behavior of stochastic linear multistep method...
The generalized Langevin equation (GLE) is a stochastic integro-differential equation that has been ...
In this article, we present several algorithms for stochastic dynamics, including Langevin dynamics ...
A fractional advection-dispersion equation (fADE) has been advocated for heavy-tailed flows where th...
A stochastic algorithm based on the Langevin equation has been recently proposed to simulate rarefie...
Turbulent reactive flow calculations are an important field of application for transported probabili...
Several Brownian Dynamics numerical schemes for treating stochastic differential equations atthe pos...
The lecture outlines the most important mathematical facts about stochastic processes which are desc...
234 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1998.Stochastic Lagrangian simulat...
The goal of this paper is to present a series of recent contributions arising in numerical probabili...
International audienceThe objective of molecular dynamics computations is to infer macroscopic prope...
In a number of problems of mathematical physics and other fields stochastic differential equations a...
Kinetic Monte Carlo methods provide a powerful computational tool for the simulation of microscopic ...
A stochastic algorithm based on the Langevin equation has been recently proposed to simulate rarefie...
This paper introduces time-continuous numerical schemes to simulate stochastic differential equation...
The aim of this talk is the analysis of the long-term behavior of stochastic linear multistep method...
The generalized Langevin equation (GLE) is a stochastic integro-differential equation that has been ...
In this article, we present several algorithms for stochastic dynamics, including Langevin dynamics ...
A fractional advection-dispersion equation (fADE) has been advocated for heavy-tailed flows where th...
A stochastic algorithm based on the Langevin equation has been recently proposed to simulate rarefie...
Turbulent reactive flow calculations are an important field of application for transported probabili...
Several Brownian Dynamics numerical schemes for treating stochastic differential equations atthe pos...
The lecture outlines the most important mathematical facts about stochastic processes which are desc...
234 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1998.Stochastic Lagrangian simulat...
The goal of this paper is to present a series of recent contributions arising in numerical probabili...
International audienceThe objective of molecular dynamics computations is to infer macroscopic prope...
In a number of problems of mathematical physics and other fields stochastic differential equations a...
Kinetic Monte Carlo methods provide a powerful computational tool for the simulation of microscopic ...
A stochastic algorithm based on the Langevin equation has been recently proposed to simulate rarefie...
This paper introduces time-continuous numerical schemes to simulate stochastic differential equation...