Study of stochastic mixing models for combustion in turbulent flows

Abstract

This study evaluates several mixing models for the prediction of combustion within a Partially Stirred Reactor (PaSR). The models considered are the Interaction by Exchange with the Mean (IEM) model, the extended IEM, Langevin and extended Langevin models. The degree of mixing and of reaction and their influence on the thermochemical properties in a combustion process are investigated. Since these mixing models involve stochastic terms, their implementation is performed by the Monte Carlo method using numerical schemes which solve the stochastic differential equations.This study consists, first, on the presentation and assessment of those mixing models in a situation in which a single scalar field is considered in the presence of a homogeneous and isotropic turbulent field. The evolution of the probability density function and the main properties for a single scalar field are studied for each mixing model. Numerical results are compared with direct numerical simulation, showing excellent qualitative and quantitative agreements.Then, the mixing models are used for numerical simulation of a PaSR where the mixing and reactive processes occur. The PaSR is used to assess the mixing model influence on the thermochemical properties of the mixture in a premixed combustion process, which is modeled using a reaction progress variable. The results obtained with the different mixing models are compared in several operating regimes of the PaSR showing that, when mixing is fast and reaction is intense, the different models lead to similar results. However, when mixing is slow and reaction is mild, important differences are observed between the models’ results.