Date of Award


Publication Type

Master Thesis

Degree Name



Mechanical, Automotive, and Materials Engineering

First Advisor

Jeffrey Defoe


Automotive fan, Computational Fluid Dynamics, Numerical Simulation, Turbomachinery, Uncalibrated Body force model, Underhood vehicle thermal management




Underhood vehicle airflow simulations are an important part of the overall vehicle thermal management process, especially in the preliminary stages of the vehicle development program when performing experimental work on cooling system prototypes can prove to be expensive, time-consuming, or simply impossible due to the absence of any physical vehicle prototypes. Accurate prediction of the automotive fan performance, which forms a critical component of the cooling module, is a prerequisite for the optimum sizing and design of heat exchangers, and the rest of the under-hood installations. The coupled and complex nature of the under-hood flow environment necessitates consideration of the entire front-end cooling module, and preferably the entire vehicle, in a single simulation to judge the fan performance. Direct modelling of the rotating fan blades in a full vehicle simulation can yield unacceptably long run times, hence the norm is to use simplified numerical models which can capture the general fan behaviour at a reduced cost. Industrial practice is to calibrate these fan models with experimental or high-fidelity simulated fan performance data, which slows down the design process and is expensive. This work solves this problem by using an uncalibrated body force fan modelling approach, which only requires fan geometry information and no a-priori fan performance data. The approach has previously shown promising results for aircraft engine fan applications, however it’s suitability for automotive fan applications is tested for the first time. The model performs with a comparable accuracy as the current state-of-the-art calibrated fan modelling techniques. It predicts the radiator airflow rate to within 8% of the experimentally-measured value at idle. At high vehicle speed, the accuracy improves to 1%. Success in this project facilitates a low-cost, reliable and rapid aerothermal analysis tool for designing vehicle cooling systems.

Available for download on Wednesday, September 15, 2021