PhD Studentship: Flow Modelling and Control for Agile Delta Wings

Aerodynamics & Flight Mechanics Group

Location: Highfield Campus

Closing Date:  Friday 01 September 2017

Reference: 822516AK

Project Reference: AACE-AFM-152

Project Themes: Fluid Dynamics, Computational Engineering

Delta wings are common platforms for investigating highly manoeuvrable and agile high-speed civil and military aircrafts. At moderate angles of attack, two counter-rotating vortical structures form at the leading edge, greatly enhancing lift. Although the time-averaged flow is symmetric, unsteady, three-dimensional features adversely impact performance characteristics and handling qualities, especially in dynamic flight conditions. Despite recent advances in understanding such key flow mechanisms, progress in the ability to design effective control strategies to manipulate their behaviour with the goal of increasing maneuverability has remained more elusive.

A promising approach towards this goal is reduced order modelling whereby complex flow dynamics are distilled into a reduced order model (ROM), a system that reproduces the main features with a greatly reduced number of degrees of freedom, hence enabling large reductions of the computational costs associated to control design and optimisation.

At high Reynolds numbers, such as those considered in this project, a key feature of the resulting ROMs is that the energy transfers between the modes of the model are sparse. Sparsity is physically determined by the inherent multi-scale nature of the turbulent flow and because the dynamics at a certain length scale are determined by the dynamics of scales of commensurate lengths and much less by significantly larger or smaller scales. Current state-of-the-art model order reduction techniques do not exploit this property and produce densely-connected ROMs. These become computationally inefficient when a large number of modes is required to describe a large number of energy–containing scales. Exploiting this sparsity is the key to retain computational efficiency in these scenarios.

The main objective of this PhD project is to develop a novel model sparsification technique, whereby sparsely-connected ROMs are synthesized from densely-connected ROMs. The focus will be on the development of data-driven methods to unravel the sparsity, using well-established statistical and machine learning techniques. High-fidelity numerical simulations of the flow around a reference delta wing geometry (see accompanying picture) will be performed on IRIDIS, the High Performance Computing facility of the University of Southampton. Control oriented sparsely-connected ROMs will be also constructed by including the effects of leading-edge actuator devices, introduced to manipulate the flow dynamics and affect handling qualities. A reduced-order, optimal control framework will then be developed to investigate control in practical applications such as highly transient maneuvers and loads alleviation in atmospheric turbulence.

We are looking for an applicant with a background in physics, aerospace/mechanical engineering, or mathematics. Programming experience in Python and/or C/Fortran languages is instrumental. One full three-year studentship is available for UK/EU students. The stipend is at the standard EPSRC levels.

If you wish to discuss any details of the project informally, please contact Davide Lasagna, Aerodynamics and Flight Mechanics research group, Email: davide.lasagna@soton.ac.uk Tel: + 0044 (023) 8059 4907

To apply please use the following link http://www.southampton.ac.uk/engineering/postgraduate/research_degrees/apply.page? and select Faculty of Engineering and the Environment.

Further details:

• Job Description and Person Specification