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.
On the long-term simulation of stochastic differential equations for predicting effective dispersion coefficients / Giona, Massimiliano; Venditti, Claudia; Adrover, Alessandra. - In: PHYSICA. A. - ISSN 0378-4371. - (2019). [10.1016/j.physa.2019.123392]
On the long-term simulation of stochastic differential equations for predicting effective dispersion coefficients
Giona, MassimilianoPrimo
;VENDITTI, CLAUDIA;Adrover, Alessandra
2019
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.File | Dimensione | Formato | |
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