Funding

Self-funded PhD students only

Project code

ENGN4930219

Department

School of Mechanical and Design Engineering

Start dates

and

Closing date

Applications accepted all year round

This PhD will be based in the School of Mechanical and Design Engineering and will be supervised by Dr Jason Knight, Dr James Buick and Dr Hom Dhakal.

The work on this project will:

  • enhance knowledge in performance and efficiency of highly flexible wing surfaces, which could be applied in aerospace and renewable energy industries
  • enhance knowledge and design competitiveness in multiple applications as diverse as Micro Unmanned Aerial Vehicles to biomedical devices amongst many others

Flexible membrane surfaces such as parachutes, sails, insect wings and heart valves deform under fluid loading. This deformation is highly non-linear and has a strong dependence on initial conditions. The accuracy of such simulations has been difficult to achieve and is highly sensitive to the parameters being used. Any small errors are amplified in subsequent simulations.

Aeroelastic divergence and flutter are complex problems and continue to receive attention in the research community (Akhaven and Ribeiro, 2018). Here, the flexural rigidity is dominant for such surfaces and this has been modeled accurately (Cisonni et al, 2017) and is also available and used in commercial codes (Ozcatalbas et al, 2018). However, for membranes, the induced tension is dominant and more unstable.

This research will investigate, in detail, the parameters used in such simulations, to assess their sensitivities. The fluid-structure interaction will be obtained using CFD coupled with a structural code. Once successfully developed, the approach will be applied to a range of industrial applications.

We have an international reputation for applied research in behaviour and mechanics of advanced materials, including numerical studies of the deformation of flexible membrane surfaces to capture fluid-structure interactions (Knight et al, 2009, 2010). The techniques developed in these works will be extended to account for complex geometries and multi-directional material properties. The work can be exploited in many applications of industrial interest.

A parallel wind tunnel experimental program with use of digital image correlation and a separate tailored in-situ micro wind tunnel test within X-ray tomography equipment will be used to generate geometry for use in and to validate findings from the numerical studies.

The assessment of a large number of design alternatives and parameters will also be investigated for performance realisation and optimisation, as well as for the generation of scaling laws.

The work will enhance knowledge around the performance and efficiency of highly-flexible wing surfaces, which could be applied in aerospace and renewable energy industries. The work will also enhance knowledge and design competitiveness in multiple applications, from Micro Unmanned Aerial Vehicles to biomedical devices, among many others.

Entry requirements

Entry requirements

  • You'll need a good first degree from an internationally recognised university (minimum second class or equivalent, depending on your chosen course) or a Master’s degree in Aeronautical, Mechanical or related engineering discipline
  • In exceptional cases, we may consider equivalent professional experience and/or Qualifications
  • English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0

How to apply

Please contact Dr Jason Knight (jason.knight@port.ac.uk) to discuss your interest before you apply, quoting the project code.

When you're ready to apply, you can use our online application form and select ‘Mechanical and Design Engineering’ as the subject area. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.

Our ‘How to Apply’ page offers further guidance on the PhD application process.

Please note, to be considered for this self-funded PhD opportunity you must quote project code ENGN4930219 when applying.

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