Electrical self-sensing in composite material
This project will extend work in to the use of carbon reinforcing fibres as electrical sensing elements in smart materials. So called self-sensing uses the reinforcing fibres to determine the state of the composite either during manufacture (cure monitoring) or through its life (condition monitoring), allowing the operator to investigate if problems arise. By monitoring resistance changes in carbon fibre composite materials during manufacture and service, it is possible to monitor either cure state of the panel or damage occurring within the panel. Two projects are available, one will examine cure using changes in electrical resistance to indicate the end of the cure process, while the second will monitor the development of damage within the structure. Both projects will seek create practical implementations of the sensors than have the potential for commercial application, while maximising the monitored area without loss of accuracy. They will involve the manufacture of carbon fibre composites using autoclave and vacuum bagging techniques, followed by testing using appropriate chemical or mechanical methods.
Candidates should be self-funded, sponsored, or applying for Scholarships. The University and the Faculty of Engineering award PhD scholarships for Home, EU, and International students on a competitive basis every year. The deadline for Faculty/University Scholarships is February each year - for more information see: www.shef.ac.uk/postgraduate/research/scholarships
Candidates should have or expect to gain a good Honours degree with 2i or above in Materials Science and Engineering or related discipline.
If English is not your first language then you must have International English Language Testing Service (IELTS) average of 6.5 or above with at least 6.0 in each component.
How good is research at University of Sheffield in Electrical and Electronic Engineering, Metallurgy and Materials?
Materials Science and Engineering
FTE Category A staff submitted: 34.80
Research output data provided by the Research Excellence Framework (REF)
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