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Title: Industrial case study-driven innovative optimised engineering design
Author: Morgan, Heather Dawn
ISNI:       0000 0004 7425 4871
Awarding Body: Swansea University
Current Institution: Swansea University
Date of Award: 2015
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Optimisation research is a vast and comprehensive field of study in academia, but its application to complex real life problems is much more limited. This thesis presents an exploration into the use of optimisation in the weight reduction problems of three industrial case studies. The work sought to find robust and practical solutions that could be exploited in the current commercial environment. The three case studies comprised the housing of a vertical axis wind turbine, a titanium jet engine lifting bracket and a casing for an aircraft cargo release system. The latter two were to be built using additive layer manufacture, while the housing, with initially no prescribed manufacturing method, was required to conform to British Standards for design. Based on commercially available optimisation and analysis packages e.g. Altair Optistruct, ANSYS, Microsoft Excel and MatLab, methodologies were developed to enable solutions to be found within realistic time-scales. Techniques to improve computational efficiency using the Kreisselmieier Steinhauser functions were also investigated. Good weight reduction was achieved in all cases. For the housing, a trend showing the relationship between the overall size of the housing and the material requirement was also developed. Extensive data for the lifting bracket was retrieved and analysed from a crowd-sourced design challenge. This highlighted important elements of design for additive layer manufacture and also gave an indication of the efficacy of different optimisation algorithms. The casing design methodology obtained simplified the material selection for the design. Build orientation software was developed to exploit the advantages of additive layer manufacture. The initial objective to solve the optimisation problems for all three case studies was accomplished using topology and size optimisation with both gradient-based and evolutionary methods. Data analysis and optimisation increased design capability for additive layer manufacture build and orientation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Eng.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available