PhD Studentship
Imaging techniques for enhancing mechanical characterisation of composite material and structures
University of Southampton
Ref: EngSci-MATS-110
Research group: Engineering Materials, Faculty of Engineering and the Environment
Deadline: Applications will be accepted at any time until the position is filled.
The project intends to apply imaging techniques as an integral part of composite materials and structural testing methodologies. The main business of Instron is in the development of materials testing machines of which we have many at UoS. The project intends to use the expertise developed at UoS in the advanced operation and control of these machines during complex material testing to underpin a new means of more effectively interpreting data from materials tests. In mechanical tests pin pointing the exact moment of failure of a composite component or structure is difficult due the complex nature of the material. The current practice is to identify failure using a global feature such as load reduction or large displacement. Here it is proposed to develop full field techniques to monitor and most importantly control tests. The techniques have the advantage that the entire component can be viewed during the test and temperature and displacement evolutions can be obtained locally during the testing. The idea is to apply these techniques across a variety of test scenarios, high speed, fatigue and quasi static to better identify failure and control the machine behaviour. For example, in determining material properties such as strain energy release rate from a crack, the crack propagates and the parameters for the test change; in load control the displacement changes and in displacement control the load changes. Here it is proposed to use the temperature evolutions at the crack-tip collected from a high speed infra-red detector to infer the energy released and thereby change the test parameters accordingly so that new test procedures can be devised where the strain energy release rate is constant. It is also proposed to use these approaches to better understand the test machine behaviour and provide feedback into test result particularly from high speed testing.
