Large Eddy Simulation in the Scalar Field

Focusing on Large Eddy Simulation (LES) in the scalar field, this work has threefold achievement: ï¼ The development, validation and application of a new anisotropy subgrid scale (SGS) model that is designed to better describe the behavior of SGS scalar flux transport In the frame of LES, a new developed anisotropy model is proposed and implemented. Unlike the isotropic SGS scalar flux models, the new model involves the anisotropic diffusivity and takes into account the scalar gradients in different directions of flows. This model is validated in different engineering related configurations of various complexities, which include a mixing layer problem, a jet in cross flow and jet in channel flow configuration. Thereby mixing processes involving low Schmidt number and high Schmidt number effects have been carefully examined. It is shown that the proposed model achieves a good agreement with the experimental data and significantly outperforms isotropic form models. ï¼ The characterization and quantification of turbulent mixing processes, in terms of scalar structures and degree of mixing along with implementation of passive and active modification techniques To provide a methodic analysis of turbulent mixing processes, a representation of mixing is involved, which includes its physical nature, scales and resolution study. With this understanding, the so-called â€Mixing parameters†are introduced. The ability of these parameters to retrieve the mixing mechanism is clearly established within different mixing processes. A mixedness parameter (MIX) can represent the probability of mixed fluids in the computational domain. The following two are the spatial mixing deficiency (SMD) and the temporal mixing deficiency (TMD) parameters for characterizing the macromixing and micromixing. ï¼ The attempt towards an optimization of mixing A numerical mixing optimization procedure is demonstrated using LES. The motivation is that LES has the approved ability to obtain detailed, accurate and comprehensive data of mixing quantities, which meets the requirement of mixing optimization design. Although the principal focus is a specific impingement mixing mixer problem, the methodology developed is equally applicable to virtually any aspect of technology and engineering, where mixing processes are important