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Methods for the efficient utilisation of dynamic CAE solvers to derive appropriate optimisation loadings for complex problems / RYAN THORNHILL

Swansea University Author: RYAN THORNHILL

DOI (Published version): 10.23889/SUThesis.69045

Abstract

Computer Aided Engineering (CAE) within the automotive sector is a constantly evolving area, with automotive manufacturers continuously seeking new techniques that will allow for an improved output within a shorter time frame, allowing them to keep up with the rapidly changing automotive market. Thi...

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Published: Swansea University, Wales, UK 2024
Institution: Swansea University
Degree level: Doctoral
Degree name: Ph.D
Supervisor: Sienz, J
URI: https://cronfa.swan.ac.uk/Record/cronfa69045
first_indexed 2025-03-06T16:24:22Z
last_indexed 2025-03-07T05:49:39Z
id cronfa69045
recordtype RisThesis
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spelling 2025-03-06T11:46:43.4389517 v2 69045 2025-03-06 Methods for the efficient utilisation of dynamic CAE solvers to derive appropriate optimisation loadings for complex problems 99bfc8f2dc92ef59858c4f0ea028f00f RYAN THORNHILL RYAN THORNHILL true false 2025-03-06 Computer Aided Engineering (CAE) within the automotive sector is a constantly evolving area, with automotive manufacturers continuously seeking new techniques that will allow for an improved output within a shorter time frame, allowing them to keep up with the rapidly changing automotive market. This challenge is more evident than ever with the automotive industry facing one of the biggest changes in its history, as it begins to move away from conventional fossil fuel internal combustion engines (ICE) to battery electric vehicles (BEV). This change is leading to a much wider range of design options and new components to be considered, therefore the ability to asses new models rapidly and accurately is key to obtaining the optimal overall vehicle package. Therefore, this thesis details a number of investigations that have been carried out researching various options to allow for reducing simulation time, whilst simultaneously improving the quality of data that can be obtained and utilised in the design and lightweighting process of future vehicle components. Key areas of focus included the assement and optimisation of a planetary gear carrier, investigations into the load extraction from various sources to aid static part optimisations. Synopsis The aim is to develop methods for the efficient utilisation of dynamic CAE solvers to derive appropriate topology loadings for complex problems. Typically, load conditions are known and for topology optimisation this then leads to the solution of a complex linear elastic problem. In realty however, loading is uncertain and varying, e.g. torque ripples in a drive train due to motor design and drive conditions, structural loading due to gust loading on for instance automotive car doors; This requires a mapping of the load space for these varied events onto the components of interest. For the first case mentioned above this leads to a very high number of simulations. The objective is to reduce the computational work for deriving the correct loading conditions in an efficient and robust manner. E-Thesis Swansea University, Wales, UK CAE, Automotive, Simulation, Low-fidelity 20 11 2024 2024-11-20 10.23889/SUThesis.69045 A selection of content is redacted or is partially redacted from this thesis to protect sensitive and personal information. COLLEGE NANME COLLEGE CODE Swansea University Sienz, J Doctoral Ph.D 2025-03-06T11:46:43.4389517 2025-03-06T11:33:14.1902296 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering RYAN THORNHILL 1 69045__33742__4304510a71054b629661b240bbd40250.pdf 2023_Thornhill_R.final.69045.pdf 2025-03-06T11:43:52.3765753 Output 20599060 application/pdf E-Thesis – open access true Copyright: The Author, Ryan Thornhill, 2023 true eng
title Methods for the efficient utilisation of dynamic CAE solvers to derive appropriate optimisation loadings for complex problems
spellingShingle Methods for the efficient utilisation of dynamic CAE solvers to derive appropriate optimisation loadings for complex problems
RYAN THORNHILL
title_short Methods for the efficient utilisation of dynamic CAE solvers to derive appropriate optimisation loadings for complex problems
title_full Methods for the efficient utilisation of dynamic CAE solvers to derive appropriate optimisation loadings for complex problems
title_fullStr Methods for the efficient utilisation of dynamic CAE solvers to derive appropriate optimisation loadings for complex problems
title_full_unstemmed Methods for the efficient utilisation of dynamic CAE solvers to derive appropriate optimisation loadings for complex problems
title_sort Methods for the efficient utilisation of dynamic CAE solvers to derive appropriate optimisation loadings for complex problems
author_id_str_mv 99bfc8f2dc92ef59858c4f0ea028f00f
author_id_fullname_str_mv 99bfc8f2dc92ef59858c4f0ea028f00f_***_RYAN THORNHILL
author RYAN THORNHILL
author2 RYAN THORNHILL
format E-Thesis
publishDate 2024
institution Swansea University
doi_str_mv 10.23889/SUThesis.69045
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering
document_store_str 1
active_str 0
description Computer Aided Engineering (CAE) within the automotive sector is a constantly evolving area, with automotive manufacturers continuously seeking new techniques that will allow for an improved output within a shorter time frame, allowing them to keep up with the rapidly changing automotive market. This challenge is more evident than ever with the automotive industry facing one of the biggest changes in its history, as it begins to move away from conventional fossil fuel internal combustion engines (ICE) to battery electric vehicles (BEV). This change is leading to a much wider range of design options and new components to be considered, therefore the ability to asses new models rapidly and accurately is key to obtaining the optimal overall vehicle package. Therefore, this thesis details a number of investigations that have been carried out researching various options to allow for reducing simulation time, whilst simultaneously improving the quality of data that can be obtained and utilised in the design and lightweighting process of future vehicle components. Key areas of focus included the assement and optimisation of a planetary gear carrier, investigations into the load extraction from various sources to aid static part optimisations. Synopsis The aim is to develop methods for the efficient utilisation of dynamic CAE solvers to derive appropriate topology loadings for complex problems. Typically, load conditions are known and for topology optimisation this then leads to the solution of a complex linear elastic problem. In realty however, loading is uncertain and varying, e.g. torque ripples in a drive train due to motor design and drive conditions, structural loading due to gust loading on for instance automotive car doors; This requires a mapping of the load space for these varied events onto the components of interest. For the first case mentioned above this leads to a very high number of simulations. The objective is to reduce the computational work for deriving the correct loading conditions in an efficient and robust manner.
published_date 2024-11-20T08:31:31Z
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score 11.056938

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