Jones, O.P.H., Oakley, J.E. orcid.org/0000-0002-9860-4093 and Purshouse, R.C. orcid.org/0000-0001-5880-1925 (2019) Toward a unified framework for model calibration and optimisation in virtual engineering workflows. In: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), 06-09 Oct 2019, Bari, Italy. IEEE , pp. 2148-2153. ISBN 9781728145709
Abstract
When designing a new product it is often advantageous to use virtual engineering as either a replacement or assistant to more traditional prototyping. Virtual engineering consists of two main stages: (i) development of the simulation model; (ii) use of the model in design optimisation. There is a vast literature on both of these stages in isolation but virtually no studies have considered them in combination. The model calibration and design optimisation processes both however, crucially, draw on the same resource budget for simulation evaluations. When evaluations are expensive, there may be advantages in treating the two stages as combined. This study lays out a joint framework by which such problems can be expressed through a unified mathematical notation. A previously published case study is reviewed within the context of this framework, and directions for further development are discussed.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Science Research Council EP/L025760/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 25 Feb 2020 10:27 |
Last Modified: | 28 Nov 2020 01:52 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/smc.2019.8914600 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157647 |