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EngSci-MATS-149: Next Generation Dynamic Fracture Methods using Ultra-High Speed Imaging

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  • Full or part time
    Prof F Pierron
  • Application Deadline
    Applications accepted all year round

Project Description

Engineering structures such as automobile frames and aircraft wings are used in demanding applications that require them to sustain high strain rate loading. Impact resistant design of these structures relies on accurate models of failure under high strain rate conditions. Despite the exponential increase in computing power to model these structures there has not been an equivalent increase in the power of experimental techniques to inform computer based material models. Therefore, the focus of the PhotoDyn research group (http://photodyn.org/) is to develop the next generation of experimental techniques to characterise high strain rate failure of materials using ultra-high speed imaging.

The aim of this project is to develop new experimental techniques for analysing the dynamic fracture toughness of materials. A combined approach of simulation and experiments will be used to develop these methods. This project will include a significant experimental component using state-of-the-art imaging and impact facilities recently commissioned for the PhotoDyn research group. During this project the candidate will receive extensive training in full-field strain measurement techniques; high strain rate impact testing methods and ultra-high speed imaging.

The ideal candidate for this project will have a bachelor or master degree in mechanical, materials or civil engineering and have studied fracture mechanics at undergraduate level. Prior experience with finite element simulations is desirable but not essential.

If you wish to discuss any details of the project informally, please contact Dr. Lloyd Fletcher, Engineering Materials research group, Email: [email protected], Tel: +44 (0) 2380 59 6626.

How good is research at University of Southampton in General Engineering?

FTE Category A staff submitted: 192.23

Research output data provided by the Research Excellence Framework (REF)

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