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QUANTIFICATION OF TURBULENT CHARACTERISTICS USING HIGH FIDELITY COMPUTATIONAL FLUID DYNAMICS FOR HEAT EXCHANGER APPLICATIONS
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Methods for transferring heat through convection are highly variable and numerous in application. Still, the principle mechanisms that drive convective heat transfer can be reduced down to thermal conditions, fluid properties, turbulent characteristics, and geometric features. Several of these principles will be analyzed through individual projects, which isolate the mechanism under consideration. Using high fidelity computational fluid dynamics (CFD), simulations that encompass variations in thermal properties in fuel rods, buoyancy driven flow within a closed system, and turbulence within a helical coil heat exchanger will be made. Turbulent statistics will be generated and then assessed through various methodologies. Sensitivity to modeling parameters, validation with experimental measurements, and analyzing higher order statistics will be some of the techniques to ensure the accuracy of the simulation. The main objective of this work is to evaluate the advantages of using high fidelity CFD for heat exchanger applications and add to the wealth of knowledge for improving modeling of complex flows. Understanding the underlying physics for each problem will enable greater confidence in identifying the aspects of a simulation that need further investigation and whether chosen assumptions are justified. Moreover, the resolution and modeling parameters have been documented as a guideline to the minimum size and cost to conduct high resolution simulations of these flows. By using scaling of geometry and Reynolds number, future engineers will be able to use these turbulent quantities as a reference to more effectively improve the efficiency and safety of new designs that involve heat exchangers.
SubjectComputational Fluid Dynamics
Spectral Element Method
Lai, Jonathan K. (2019). QUANTIFICATION OF TURBULENT CHARACTERISTICS USING HIGH FIDELITY COMPUTATIONAL FLUID DYNAMICS FOR HEAT EXCHANGER APPLICATIONS. Doctoral dissertation, Texas A & M University. Available electronically from