Stochastic Lagrangian Modeling for Large Eddy Simulation of Dispersed Turbulent Two-Phase Flows

Stochastic Lagrangian Modeling for Large Eddy Simulation of Dispersed Turbulent Two-Phase Flows

Indexed in: Scopus

Understanding the dispersion and the deposition of inertial particles convected by turbulent flows is a domain of research of considerable industrial interest. Inertial particle transport and ...
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Introduction

Pp. 3-5 (3)

Abdallah Sofiane Berrouk

Abstract

Understanding the dispersion and the deposition of inertial particles in turbulent flows is a domain of research of utmost practical interest. With advances in computing resources, Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) have become powerful tools for the investigation of particle-laden turbulent flows with the hybrid Eulerian-Lagrangian approach playing a key role in predicting inertial particle dispersion and deposition. Computational intractability that arises due to the need of solving all the scales has restricted DNS to the very low Reynolds number turbulent flows that are not often of practical interest. LES, by solving only the large energy-containing eddies and modeling the small quasi-universal scales, is relaxed from this restriction. Thus, tackling high Reynolds number turbulent flow becomes possible. The use of large-eddy simulation has increased over the years as a promising tool to address these types of problems with the required accuracy at an affordable computing cost. In LES of dispersed turbulent multiphase flows, it has been common that tracking inertial particles in turbulent flows is carried out using only the filtered velocity field. This turned out to be inaccurate for cases dealing with very small, turbulence-responsive particles. For these cases, the timedependent velocity field seen by the inertial particles can be stochastically constructed in a Lagrangian framework. This can be achieved through the use of a stochastic diffusion process such as Langevin models.

Keywords:

Large eddy simulation, turbulent flows, Eulerian-Lagrangian, sub-grid scales, filtered velocity, stochastic process, diffusion, dispersion, deposition, inertial particles

Affiliation:

Chemical Engineering Department Petroleum Institute, Abu Dhabi United Arab Emirates