Mechanical Engineering ETDs

Publication Date

Fall 12-30-2023

Abstract

Mixing layer flow is one of the canonical free shear flows in fluid dynamics. Such a flow is formed when two fluid streams move along one another with different velocities. Investigation of this flow development has been an active topic of research for many decades not only due to a wide range of environmental and technological applications where this flow may be observed, but also because of large discrepancies in the results obtained experimentally and numerically regardless this flow simple geometry. In this dissertation, the quality and uncertainty of extracted turbulent statistics of mixing layer flow are analyzed by applying the RANS-DNS framework proposed in Poroseva et al. (2016). Before collecting the statistics, the self-similarity of a spatially developing mixing layer flow problem is thoroughly analyzed using the produced DNS data in Colmenares (2019). Once the flow self-similarity region is identified, turbulent statistics including higher order moments and their transport equations budget terms are collected and analyzed within this region. The RANS-DNS simulations are conducted using the open-source CFD solver OpenFOAM. This solver is also validated by simulating a two-dimensional mixing layer benchmark case, available at the NASA Turbulence Modeling Resource (TMR) website.

Keywords

Computational fluid dynamics, Fluid dynamics simulation, Turbulent flows, Free-shear layers, Turbulent flows simulation.

Degree Name

Mechanical Engineering

Level of Degree

Doctoral

Department Name

Mechanical Engineering

First Committee Member (Chair)

Prof. Svetlana V. Poroseva

Second Committee Member

Prof. Edl Schamiloglu

Third Committee Member

Prof. Peter Vorobief

Fourth Committee Member

Prof. Yulia Peet

Document Type

Dissertation

Language

English

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