Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.791201
Title: Advances in computational engineering for sustainable energy generation
Author: Hewitt, Sam
ISNI:       0000 0004 8501 2050
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2019
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Abstract:
Over the past decades, the scientific and engineering communities have spent a lot of time on the development of sustainable energy solutions, to combat the adverse effects that non-renewable energy sources are having on the climate. Computational modelling has played a significant role in the advancement and evolution of novel technologies to capture energy from renewable sources. The capabilities of computational models to simulate complex physics is growing with improved numerical modelling techniques and increasing levels of computing power. The purpose of this work is to develop the predictive modelling capabilities of computational simulation tools for sustainable energy applications. This is achieved through the development of a multiphysics tool to solve the coupled interaction of a fluid and a structure. The numerical tool is used to study the fundamental fluid dynamics processes that occur when a fluid interacts with a flexible structure. Further to this, an advanced structural model, capable of predicting damage in dynamically loaded structures was developed and evaluated. Testing and evaluation of the numerical tools developed, highlighted their capability to effectively use high performance computing services to model complex coupled physics problems. Numerical studies of a flexible structure highlighted a number of phenomena. Including, the emergence of a periodic deflection of the structure and the destabilising effects of the structures motion on the flow field. This work will be of interest to researchers and scientists interested in the current capabilities of academic computer aided engineering software for extreme scale computers.
Supervisor: Revell, Alistair ; Afgan, Imran ; Margetts, Lee Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.791201  DOI: Not available
Keywords: Fluid-structure interaction ; High performance computing ; Multiphysics ; Multiscale modelling
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