RANS Turbulence Modelling for Motorsport Applications

Abstract

This thesis is investigating the applicability of a range of newer RANS models with corrections for certain flow features to industrial flows, using the motorsport industry as the target applica- tion industry. The motorsport industry is dominated by rigid regulations and time constraints, therefore RANS models are the only feasible solution, providing strong scope for research into improving existing schemes. Recent research on RANS focused on sensitizing the models to flows with streamline curva- ture/system rotation and stress-strain lag. In this thesis, these types of corrections are assessed from a fundamental turbulence modelling perspective, where the contribution of all the terms in the transport equations is investigated and the mechanism through which they improve turbulence predictions is laid out. The analysis is performed on cases of classic homogeneous turbulence, using an in-house code developed by the author, TAMARIND. Furthermore, a range of these models with corrections is further tested in more complex cases using Star-CCM+ as a commercial solver. Particularly encouraging results are obtained from TAMARIND with the C as − k − ε model for flows with stress-strain lag. The Lag-EB-k − ε turbulence model is a further development of the aforementioned model which is implemented in Star-CCM+. Therefore, the focus is then di- rected on the performance of this model, firstly compared to other available RANS models then secondly a mesh sensitivity analysis is conducted to determine the effects of mesh resolution on the model’s performance for the latter part of the thesis. As the example industrial target application is the motorsport industry, the last test case pre- sented here is the Imperial Front Wing, which is a simplified geometry of a typical open-wheel racing car. The Imperial Front Wing geometry was supplied as part of a collaborative project between The Mechanical, Aerospace and Civil Engineering (MACE) School at The University of Manchester and McLaren Racing Limited.

Date of Award	1 Aug 2018
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Timothy Craft (Supervisor) & Alistair Revell (Supervisor)