Abstract

Turbulent mixing plays a central role in a wide range of engineering and natural systems, particularly in reactive flows where turbulence--chemistry interactions strongly influence reaction rates, flame structure, and emissions. Accurately modeling these interactions remains a major challenge due to the multiscale and stochastic nature of turbulence, as well as the nonlinear coupling between transport and chemical kinetics. This dissertation develops and evaluates the Hierarchical Parcel Swapping (HiPS) model, a fully stochastic framework designed to represent turbulence-driven transport and scalar mixing without relying on traditional gradient-based closures. HiPS is investigated both as a standalone turbulence model and as a subgrid scalar mixing model within the transported probability density function (PDF) methodology. The work examines the ability of HiPS to reproduce key statistical features of turbulence, including pair dispersion, scalar dissipation, and inertial-range scaling behavior. An analytical formulation of pair dispersion on the HiPS tree is developed and shown to recover classical Richardson scaling in the inertial range, as well as lognormal statistics in the viscous range. A standalone C++ implementation of HiPS has also been developed to enable efficient numerical experimentation and integration with existing simulation frameworks. Finally, HiPS is applied as a mixing model within the transported PDF framework and compared against established approaches such as Interaction by Exchange with the Mean (IEM) and Modified Curl (MC) models.

Degree

PhD

College and Department

Ira A. Fulton College of Engineering; Chemical Engineering

Rights

https://lib.byu.edu/about/copyright/