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NGCM-0076: Flow Modelling and Control for Agile Delta Wings.

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  • Full or part time
    Dr D Lasagna
    Dr A Da Ronch
  • Application Deadline
    Applications accepted all year round

Project Description

Delta wings, a paradigmatic configuration of highly swept 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 generally symmetric, unsteady, three-dimensional features such as vortex wandering, breakdown, instability, flow separation and reattachment adversely impact performance characteristics, maneuvrability and handling qualities, especially in highly dynamic flight conditions. Despite recent advances in understanding key mechanisms in unsteady vortical flows past highly-swept wings, progress in the ability to design effective flow control strategy to manipulate their spatio-temporal behaviour with the goal of increasing maneuverability, has remained more elusive.

A promising strategy to achieve this goal lies in reduced order modelling, a key area of research in computational modelling, consisting in distilling the complex dynamics of a high-dimensional system in a greatly reduced number of degrees of freedom, enabling huge reductions of the computational costs in many problems of optimisation, control and design. A distinguishing feature of nonlinear ROMs of high-Reynolds-number flows is the large sparsity that exists in the linear/nonlinear energy transfers between the modes, the interconnected components of the model. This sparsity is physically determined by the inherent multi-scale nature of turbulent motion that results in a huge disparity in length scale across energy-containing and dissipative modes. Exploiting this feature holds promise to dramatically decrease the computational costs associated to the models, because sparse systems have few interconnected components that need to be evaluated to propagate the dynamical system forward. Advances in computational methods to construct reduced order models (ROMs) of unsteady vortical flows hold promise to improve controllability of the flow around delta wings and increase the aerodynamic performance.

The objective of this PhD project will be to develop a hierarchy of control-oriented nonlinear ROMs of unsteady vortical flows past the SACCON configuration, a delta wing geometry which has been designed for research purposes. The focus will be on the development of new sophisticated methods to unravel and exploit sparsity, borrowing techniques from statistics and machine learning. Algorithmically, this work will be grounded on sparse regression methods, namely L1-based regression algorithms such as LASSO or LARS. High-fidelity numerical simulations of the flow around the delta wing geometry will be performed in a first stage on the High Performance Computing facilities of the University of Southampton to generate a large flow database. Sparsity preserving ROMs will be then constructed by mining this database and will be used to extract physical insight into low-dimensional aspects of the flow dynamics. In a second stage, control oriented ROMs will be 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.

The ideal candidate has completed a degree in Aerospace, Mechanical or Computational engineering. Programming experience in Python and/or C/Fortran languages is instrumental, as well as familiarity with parallel programming and a natural inclination for mathematical modelling.

If you wish to discuss any details of the project informally, please contact Davide Lasagna, Aerodynamics and Flight Mechanics group, Email: [email protected], Tel: +44 (0) 2380594907.

This project is run through participation in the EPSRC Centre for Doctoral Training in Next Generation Computational Modelling ( For details of our 4 Year PhD programme, please see

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