Experimental and numerical assessment of composite structural joints for virtual certification

Supervisory Team: Stephen Boyd, Janice Barton

This project exploits expertise at University of Southampton and Bristol and will employ the use of the world leading experimental test facilities in the National Infrastructure Laboratory on the Boldrewood Campus (Southampton).  Experimental full field Digital Image Correlation and Thermographic imaging will be used to establish deviations between physical and simulated tests of a typical structural assembly.

Composite materials are at the forefront of airframe technologies successfully providing reliable and high performance aerospace structures.  A key barrier to greater deployment of next generation composites for new and novel vehicle concepts is the time and cost associated with certification of new designs.

The current approach, driven by regulatory requirements, necessarily relies on physical test supported by simulation, is slow and expensive. This approach is heavily biased towards physical testing because it is currently the only reliable way to assess how inherent variabilities influence the relationship between the materials, manufacturing process and structural performance of the airframe design.

This project aims to develop and validate an emerging solution using a new statistical framework to design, model and test representative structural elements/components in order to safely account for known and unknown inherent uncertainties. The novel approach deploys multi-scale FE modelling emulators and deep learning techniques in conjunction with full-field data rich test regimes. The resulting data fusion and Bayesian analysis is able to predict probability of achieving strengths above design limit loads. This approach promises to develop virtual test techniques that can predict the real-life distribution of failure strengths and thus assign a stochastic risk factor to the simulated strength.

The student will be primarily based/supervised in the School of Engineering at the University of Southampton and co-supervised at the University of Bristol where they will have visiting student status for access to supplementary facilities and expertise.

Entry Requirements

The successful candidate MUST be a UK national. Applicants will ideally have, or expect to receive, a first class degree or equivalent in a mechanically based engineering subject or in physical sciences. A 2:1 UK honours degree or equivalent may suffice when combined with other relevant experience and/or evidence of excellence. You will have a proven track record in planning and conducting detailed experiments involving DIC or other optical techniques together with some prior experience of computer modelling and coding such as Python or Matlab.

Closing date: 31 August 2025. Applications will be considered in the order that they are received, the position will be considered filled when a suitable candidate has been identified.

Funding: This PhD opportunity is fully funded by an EPSRC iCASE Foundation PhD award through BAE SYSTEMS. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.

How To Apply

Apply online:  Search for a Postgraduate Programme of Study (soton.ac.uk) Select programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences, next page select “PhD Eng & Env. (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Prof Stephen Boyd

Applications should include:

Research Proposal

Curriculum Vitae

Two reference letters

Degree Transcripts/Certificates to date

For further information please contact: feps-pgr-apply@soton.ac.uk