Date of Award

2020

Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy in Mechanical Engineering-Engineering Mechanics (PhD)

Administrative Home Department

Department of Mechanical Engineering-Engineering Mechanics

Advisor 1

Abhijit Mukherjee

Advisor 2

Craig Friedrich

Committee Member 1

Fernando Ponta

Committee Member 2

Seong-Young Lee

Committee Member 3

Gustavo Ledezma

Abstract

This study investigates the accuracy of Computational Fluid Dynamics (CFD) models to predict heat transfer in turbulent separated flows at low Reynolds numbers. A novel improvement of a Scale Adaptive technique is also presented. A spectrum of turbulence models is used to simulate flow and heat transfer of two geometries; fully developed flow through a staggered tube bank and a square prism in cross flow. Experimental data for both local heat transfer and velocity data are available in the literature for these cases and have been used extensively evaluate various CFD methods. Six unsteady models were used and the results show that the unsteady Shear Stress Transport (SST) model provided good overall accuracy relative to the mean Nusselt number for both cases. However, the SST model failed to accurately predict local variations. The Partially Averaged Navier-Stokes variant of the SST model showed a marked improvement for both cases. The Dynamic Smagorinsky Large Eddy Simulation (LES) showed a much-improved fidelity to the local Nusselt but under predicted the actual values. The computational cost for the LES model was significant. In general, it was found that the computationally expensive models with higher degrees of resolved turbulence did not necessarily return more accurate results.

A Scale Adaptive Simulation (SAS) modification of the SST model (SAS-SST) is also used in this study. The SAS approach for the SST model adjusts the production term of the specific dissipation transport equation based on the second velocity derivative. This modification is intended to improve the SST model where local flow accelerations/ xx decelerations are detected, as occurs in separated flows. However, the local Nusselt number for the two cases considered were found to be generally less accurate than the baseline SST model. In this study a novel modification to this model was made to reduce the SAS contribution near stagnation points in the simulation. This was done through the Kato-Launder and production limiter modification in the SAS production term. The results showed only a slight improvement of the accuracy of the Nusselt number predictions. It is possible that further adjustments to the SAS terms and constants can be made to properly support and complement the stagnation point modification in this study and yield an overall better turbulence model.

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