On the long-term simulation of stochastic differential equations for predicting effective dispersion coefficients

Massimiliano Giona, Claudia Venditti and Alessandra Adrover

Physica A: Statistical Mechanics and its Applications, 2020, vol. 543, issue C

Abstract: 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.

Keywords: Stochastic differential equations; Operator splitting; Mollification; Generalized Poisson–Kac processes; Dispersion properties (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:543:y:2020:i:c:s0378437119318953

DOI: 10.1016/j.physa.2019.123392

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