Large-Eddy Simulation of Turbulent Scalar Transport Processes in Smooth and Rough Wall Boundary Layers

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In mechanical, environmental and chemical engineering, turbulent transport of active and passive scalars in a boundary layer is a frequently encountered phenomenon, which has important applications for the engine industry, power plants, building environment, and prediction of air pollution in the atmospheric boundary layer. By their nature, turbulent convective flows driven by shear stresses, pressure gradients and scalar gradients are unsteady, and exhibit coherent flow structures that are highly interactive with the scalar transport processes. The proposed research aims at obtaining a deeper understanding of the interaction between dynamically evolving flow structures and scalar transport processes in both smooth and rough-wall boundary layers using the method of large-eddy simulation (LES), as well as development of new physics-based subgrid-scale scalar-flux models for improved LES of turbulent scalar transport in both low- and high-Reynolds number flows. In order to achieve these goals, both a priori and a posteriori LES methods will be employed for testing the model performance in contexts of smooth-wall boundary-layer flows and turbulent boundary-layer flows over obstacle arrays. The obtained LES results will be validated against direct numerical simulation (DNS) data and two sets of comprehensive water-channel and wind-tunnel experimental data. It is anticipated that the proposed research will provide an excellent opportunity for the applicant and his team to conduct innovative research on development of a high-fidelity predictive tool that can be used by both academics and engineers for assessing active and passive scalar transport in different types of boundary-layer flows. It is also anticipated that the proposed research will provide an opportunity to train highly qualified personnel in areas related to computational fluid dynamics, turbulent heat and mass transfer, environmental dispersion, and high-performance scientific computing based on in-house codes and supercomputers.