Yang, Jiannan orcid.org/0000-0001-8323-7406, Langley, Robin S. and Andrade, Luis (2022) Digital twins for design in the presence of uncertainties. Mechanical Systems and Signal Processing. 109338. ISSN 1096-1216
Abstract
Successful application of digital twins in the design process requires a tailored approach to identify high value information from the uncertain data. We propose a non-intrusive sensitivity metric toolbox that integrates black-box digital twins in the design and decision process under uncertainties. The toolbox captures the evolving nature of the key design performance indicators (KPI) and provide both KPI-free and KPI-based metrics. The KPI-free metrics, which are based on entropy and Fisher information but independent of design KPIs, is shown to give good indication of the most influential data for KPI-based metrics. This suggests a consistent identification of high value data throughout the design process.
Metadata
Authors/Creators: |
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Copyright, Publisher and Additional Information: | Funding Information: This work has been funded by the Engineering and Physical Sciences Research Council through the award of a Programme Grant “Digital Twins for Improved Dynamic Design”, Grant No. EP/R006768. Publisher Copyright: © 2022 The Author(s) |
Keywords: | Design entropy, Design key performance indicator, Design sensitivity toolbox, Fisher information, Likelihood ratio method, Probability of acceptance |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Physics (York) |
Depositing User: | Pure (York) |
Date Deposited: | 03 Jan 2024 12:40 |
Last Modified: | 03 Jan 2024 12:40 |
Published Version: | https://doi.org/10.1016/j.ymssp.2022.109338 |
Status: | Published |
Refereed: | Yes |
Identification Number: | https://doi.org/10.1016/j.ymssp.2022.109338 |
Related URLs: |
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Description: Digital twins for design in the presence of uncertainties
Licence: CC-BY 2.5