PhD Studentship: Large-Scale High-Fidelity Experiments of Flow Past Bluff and Aerodynamic Bodies to Aid Data-Driven Design

University of Southampton - Aerodynamics and Flight Mechanics, Faculty of Engineering and the Environment

Innovative engineering design and optimisation requires low-cost high-fidelity predictive tools. This is especially true in systems where fluid-flows play a significant role. The new modelling strategies are still validated using point measurement data that are obtained using traditional measurement techniques. Consequently, there is potential for huge uncertainties in the predictions obtained using these models. Recent advances in flow measurement techniques allow us to obtain 2D and 3D measurements in smaller-scale facilities, which allows access to previously inaccessible data that can be used to understand new physics as well as develop a modelling paradigm that uses this detailed high-fidelity data. In this project, the goal is to scale-up these measurement techniques and obtain high-fidelity data at higher Reynolds numbers and larger-scales. You will have a unique opportunity to design and deploy a large-scale Planar and Volumetric flow measurement techniques in a state-of-the-art experimental facility (RJ Mitchell Wind tunnel, https://www.southampton.ac.uk/engineering/research/facilities/360/wind_tunnel_r_j_mitchell.page) to capture detailed information about the flow past a bluff body (such as a car model or a cyclist) and aerodynamic bodies (such a wing near-stall). The 2D and 3D measurements obtained from these laser diagnostic experiments will not only be analysed to understand the flow mechanisms involved in these flows but also be used as an input to develop data-driven CFD models that can further be used for predictions. The ultimate goal is to seamlessly integrate these large-scale measurements in a design-loop where there is synergetic information exchange between large-scale wind tunnel experiments and computational predictive strategies.

The ideal candidate will have a first-class or 2:1 degree in Engineering (preferably in Aeronautics/Aerospace Engineering) with a keen interest for experimental work and programming skills to analyse the data.

If you wish to discuss any details of the project informally, please contact Bharathram Ganapathisubramani, Aerodynamics and Flight Mechanics research group, Email: g.bharath@soton.ac.uk, Tel: +44 (0) 2380 59 2305.

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Type / Role:

PhD

Location(s):

South East England