Digital twins for design in the presence of uncertainties
| cam.depositDate | 2022-05-29 | |
| cam.issuedOnline | 2022-05-28 | |
| dc.contributor.author | Yang, J | |
| dc.contributor.author | Langley, RS | |
| dc.contributor.author | Andrade, L | |
| dc.contributor.orcid | Yang, J [0000-0001-8323-7406] | |
| dc.contributor.orcid | Andrade, L [0000-0003-0679-9354] | |
| dc.date.accessioned | 2022-05-30T23:30:30Z | |
| dc.date.available | 2022-05-30T23:30:30Z | |
| dc.date.issued | 2022 | |
| dc.date.updated | 2022-05-29T20:08:07Z | |
| dc.description.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. | |
| dc.identifier.doi | 10.17863/CAM.85031 | |
| dc.identifier.eissn | 1096-1216 | |
| dc.identifier.issn | 0888-3270 | |
| dc.identifier.uri | https://www.repository.cam.ac.uk/handle/1810/337624 | |
| dc.language.iso | eng | |
| dc.publisher | Elsevier BV | |
| dc.publisher.department | Department of Engineering | |
| dc.publisher.url | http://dx.doi.org/10.1016/j.ymssp.2022.109338 | |
| dc.rights | Attribution 4.0 International | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Design sensitivity toolbox | |
| dc.subject | Design key performance indicator | |
| dc.subject | Design entropy | |
| dc.subject | Fisher information | |
| dc.subject | Probability of acceptance | |
| dc.subject | Likelihood ratio method | |
| dc.title | Digital twins for design in the presence of uncertainties | |
| dc.type | Article | |
| dcterms.dateAccepted | 2022-05-20 | |
| prism.endingPage | 109338 | |
| prism.number | 109338 | |
| prism.publicationDate | 2022 | |
| prism.publicationName | Mechanical Systems and Signal Processing | |
| prism.startingPage | 109338 | |
| prism.volume | 179 | |
| pubs.funder-project-id | Engineering and Physical Sciences Research Council (EP/R006768/1) | |
| pubs.licence-display-name | Apollo Repository Deposit Licence Agreement | |
| pubs.licence-identifier | apollo-deposit-licence-2-1 | |
| rioxxterms.type | Journal Article/Review | |
| rioxxterms.version | VoR | |
| rioxxterms.versionofrecord | 10.1016/j.ymssp.2022.109338 |
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