Dr W Wang
Applications accepted all year round
Self-Funded PhD Students Only
About the Project
The project aim to develop a data fusion framework to validate models in multi-physics and multi-scale computational mechanics so that decision making can be more reliable for design and analysis in engineering mechanics.
Energy efficiency is one of the major challenges today. To design greener products and systems, engineers need to reduce material usage and/or apply lightweight composite materials. This may increase the risk of structural failure due to less material to bear mechanical loads and the complex failure mechanism of composites. Computer simulation offers powerful tools to assess structural reliability of the new designs. However, computational models are only as good as their assumptions. Comprehensive experimental validation with uncertainty quantification is necessary to assure the model’s credibility. This project will aim for developing a validation metric from multiple sources of measurements so that confident model prediction can be achieved.
Objectives
(1) Benchmark models in computational mechanics will be investigated in the fashion of multi-physics and multi-scales
(2) Multiple sensing technologies will be applied to capture experimental responses on the real structures corresponding to the benchmark models.
(3) Error analysis and reduction between computational and experimental data will be carried out to understand the discrepancy.
(4) Data fusion framework on multi-physics and multi-scale models will be developed to assist decision making for design and analysis in engineering mechanics.
Funding Notes
First degree (2:1 or above) in Mechanical Engineering or in Applied Mathematics
Good understanding of Computational Mechanics (e.g. finite element methods);
Knowledge of full-field experimental mechanics (e.g. digital image correlation);
PLEASE NOTE: CVS ARE NOT ACCEPTED, PLEASE COMPLETE THE APPLICATION FORM IN THE LINK BELOW.
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