|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||£18,000 per annum for four years|
|Placed On:||8th June 2023|
|Closes:||7th September 2023|
Applications are invited for a PhD position at the University of Nottingham. The successful applicant will contribute to advancing industry relevant high-fidelity finite element modelling approaches. More specifically, the successful applicant will utilise and develop advanced numerical error estimator techniques in the multiscale analysis of large aerospace structures. A modelling framework will be produced that furnishes practicing engineers with a greater understanding of how their components can deform and fail in operation. The successful candidate will have a first-class or upper second-class honours degree in mechanical engineering or a related subject.
This studentship will attract a stipend of £18,000 per annum for four years. The position arises from a long-standing engineering research relationship between the University of Nottingham and Rolls-Royce plc. The University of Nottingham hosts two of the (~30) University Technology Centres (UTCs) used by the company as the main engines of its engineering research and development. Nottingham’s UTC in Gas Turbine Transmissions Systems will host this studentship and the candidate will sit within a community of ~20 PhD students at various stages of their study. The topic of the studentship is part of a grander research aim that has been developed between academics at the University of Nottingham and Queen’s University, Belfast. As such, the successful applicant will have ample opportunity to benefit from cross-institution collaboration.
Efficiently designing large aerospace structures in a way that is both safe and makes the best use of consistent materials demands advanced simulation methods. Engineers must be able to determine where low fidelity methods are appropriate so that computational costs do not become prohibitively large and thus impede the iterative design process. Simultaneously, engineers need to identify when detailed high fidelity models are required so that key design questions (often relating to premature failure) can be satisfactorily answered. In all cases, confidence bounds and error estimates should be developed so that results can be properly contextualised. The practice of interpreting CAD models and generating multiscale analytical models is a complex one that often requires a great deal of manual intervention. The chance for user error is maximised by such approaches and modifications to analysis procedures (developed with new understanding of fundamental phenomena) become difficult to uniformly implement. What is needed is a toolbox of utilities that automates the procedure. Consistent analyses are thus created and the tedium of repeated multiscale scale analyses is alleviated. The studentship described here will contribute to the development of an automated system that formalises the multiscale application and solution process. The student will focus on the development of high-fidelity local models of composite components. Non-linear and failure responses will be incorporated in these models, along with quantity of interest driven error metrics. Machine learning approaches will be implemented to alleviate computational overhead where possible.
This project is available from 1st October 2023. Applications accepted until post is filled. Informal inquiries can be made via email to Dr James Rouse (firstname.lastname@example.org).
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
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