Development of Bayesian and Evolutionary Optimisation Approaches for Computational Aerodynamic Optimisation of Supersonic Intakes

In order to build upon the existing research collaboration between REL and Swansea University in the field of CFD-based optimisation approaches for aerodynamic design utilising Bayesian and evolutionary methods this PhD proposal has been developed. Existing methods, developed by PhD student Ben Smith, which couple a new, robust and versatile mesh morphing approach, using Radial Basis Functions, has been shown to work effectively in the aerodynamic optimisation of transonic and low supersonic bodies with external flow fields.

In the current work the approach has been applied to demonstrate potential drag reductions of the Skylon spaceplane across the transonic regime.

The natural extension of this work, given REL's interests in developing and optimizing high speed intakes for their SABRE propulsion system, is to apply the mesh morphing techniques to more challenging (aerodynamically) problems including high Mach intakes. This will involve understanding the behaviour, and validation, of the CFD solver utilised in this work (FLITE3D) along with modification of the existing (mesh based) parameterization scheme.

This will be required to allow it to be applied to the complex geometry and internal flow field found within intake systems. The proposed candidate, Rebecca Durrant, has already been working in this field as an MSc student, sponsored by REL, and to fully develop this work a PhD project is now required.

The project will lead to an enhanced optimisation toolkit, exploiting the global searching and inherent uncertainty analysis of Bayesian and evolutionary processes, that can be used on a range of fluids problems across REL's portfolio of interests.