Modelling damage and failure of structural glass panels based on a hybrid plate element

The tensile strength of thin glass panels/plates used in building structures is of great importance due to the designer’s increasing demands for such structures, regarding size, shape and weight of the panels. It is well known that the intrinsic, (for panels with perfect surfaces) tensile strength of a panel greatly exceeds the tensile strength of real panels with surfaces flaws such as surface cracks and pits. Such surface flaws can arise from manufacture of a glass panel, during handling or installation on a building, or by impact damage from wind driven debris during its service life. A major difficulty in determining the panel tensile strength in situ is the fact that the number, size and the location of the flaws on the panel surfaces are not known. Thus, in modelling a panel one requires not only numerical methods such as finite elements, but also statistical methods to predict the probability of failure for a real panel with the surface flaws subjected to a specific loading regime.

We are seeking a PhD student with appropriate background to work on the development of a modelling approach based on Kirchhoff plate theory where the biharmonic operator is split allowing for separation of the damage effects from the response of the perfect plate with no imperfections leading to coupled second order PDEs. This will enable calculation of the deformation of the plates with the randomly located and increasing number of surface flows (cracks & pits). In this the effect of the change of surface shape on the deformation is treated by having in the PDE the effect of the changing shape contained on the right-hand side of the continuous problem and the resulting matrix system in the FE computation. The random location of the increasing number of the flows are calculated using Monte-Carlo method. This new computational tool will be validated and applied to selected industrial problems.

The research involves applied mathematics and scientific computing (in, for example, Fortran or C/C++). Applicants are expected to have at least a 2.1 BSc/BEng honours degree or equivalent in Mathematics, Mechanical Engineering or a related subject.

The ideal candidate will have experience of numerical approximation of partial differential equations, although candidates lacking that specific experience should not be deterred from applying.

Note that a condition of the appointment is the requirement to complete the Graduate Learning and Teaching Programme (or equivalent) and the appointee may be required to successfully pass selected taught modules run by Brunel University London and/or the London Taught Course Centre.

This research will be carried out in at the National Structural Integrity Research Centre (NSIRC Brunel) in Cambridge and consequently the student will work at NSIRC for a certain percentage of time.

How to apply

If you are interested in applying for the above PhD topic please follow the steps below:

Contact the supervisor by email or phone to discuss your interest and find out if you would be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.

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This is a self funded topic

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.