Computational investigation of rotorcraft avionics bay cooling system

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2019
Akın, Altuğ
Computational investigation of a rotorcraft avionics bay cooling system is performed. Within the introduced system, the ambient air is supplied to the avionics-bay by a fan and exhausted back into the ambient after cooling the equipment inside. Depending on the fan and exhaust locations, hot zones may form around some of the equipment. The fan must provide a sufficiently high mass flow rate to keep the temperatures of the avionics equipment below the limits, while avoiding excessive amount of cooling to reduce power consumption. In this study, the effects of the fan and exhaust locations on the required mass flow rate are investigated. Prediction functions with Gaussian Process Regression and Artificial Neural Network methods are built to predict avionics surface temperatures using the results from a series of Computational Fluid Dynamics (CFD) analyses. The first method is selected over the latter as it yields more accurate results. The selected prediction function is used in conjunction with an optimization algorithm to determine the optimum fan and exhaust locations that minimize the required mass flow rate. It is found out that the required mass flow rate significantly depends on the fan location, while, the exhaust location has a relatively lessened effect. The required mass flow rate could be reduced to around half of its value with an even more significant reduction in power consumption. Additionally, the CFD analysis for the optimum fan and exhaust locations are repeated with different turbulence models to evaluate the effect of the selected model on the results.

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Citation Formats
A. Akın, “Computational investigation of rotorcraft avionics bay cooling system,” Thesis (M.S.) -- Graduate School of Natural and Applied Sciences. Aerospace Engineering., Middle East Technical University, 2019.