Date of Graduation

5-2023

Document Type

Thesis

Degree Name

Bachelor of Science in Mechanical Engineering

Degree Level

Undergraduate

Department

Mechanical Engineering

Advisor/Mentor

Walters, D. K.

Committee Member/Reader

Leylek, James

Abstract

The jet in crossflow is a canonical flow feature in many natural and engineered systems, ranging from pollutant dispersal in exhaust discharge to film cooling of high-temperature components in modern propulsion systems. The ability to computationally predict the flow features of jets in crossflow accurately and efficiently is therefore important for analysis and design for a wide variety of applications. In this study the capabilities of the dynamic hybrid RANS-LES (DHRL) turbulence modeling technique are investigated and compared to an industry standard Reynolds-averaged Navier-Stokes model (k-omega SST) in order to quantify the accuracy and computational cost of the two approaches. CFD simulations of a square vertical jet issuing into a wall-bounded crossflow were performed. The DHRL model can help optimize turbulence simulations by using RANS modeling where there are relatively low amounts of resolved turbulent fluctuations, and using large-eddy simulation (LES) modeling where there are relatively high amounts of resolved turbulence in the domain. This both increases the prediction accuracy where needed, while saving on computing cost by using the computationally cheaper RANS modeling for the rest of the domain. Simulations were run for three different jet-to-crossflow velocity ratios using both models. To validate the computational results, the jet flow Reynolds number, density ratio, and velocity ratios were selected to match those used in a previously published experimental study [1]. Velocity measurements obtained from the experimental data plots were then compared to the corresponding velocity measurements obtained from the results of both the DHRL and the RANS model.

Keywords

jet in crossflow, blowing ratio, RANS k-omega SST, dynamic hybrid RANS-LES

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