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Article: Isogeometric Fatigue Damage Prediction in Large-Scale Composite Structures Driven by Dynamic Sensor Data
Title | Isogeometric Fatigue Damage Prediction in Large-Scale Composite Structures Driven by Dynamic Sensor Data |
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Authors | |
Keywords | Kirchhoff-Love shells DDDAS digital twin fatigue damage IGA |
Issue Date | 2015 |
Citation | Journal of Applied Mechanics, Transactions ASME, 2015, v. 82, n. 9 How to Cite? |
Abstract | Copyright © 2015 by ASME.In this paper, we combine recent developments in modeling of fatigue-damage, isogeometric analysis (IGA) of thin-shell structures, and structural health monitoring (SHM) to develop a computational steering framework for fatigue-damage prediction in full-scale laminated composite structures. The main constituents of the proposed framework are described in detail, and the framework is deployed in the context of an actual fatigue test of a full-scale wind-turbine blade structure. The results indicate that using an advanced computational model informed by in situ SHM data leads to accurate prediction of the damage zone formation, damage progression, and eventual failure of the structure. Although the blade fatigue simulation was driven by test data obtained prior to the computation, the proposed computational steering framework may be deployed concurrently with structures undergoing fatigue loading. |
Persistent Identifier | http://hdl.handle.net/10722/235952 |
ISSN | 2023 Impact Factor: 2.6 2023 SCImago Journal Rankings: 0.726 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Bazilevs, Y. | - |
dc.contributor.author | Deng, X. | - |
dc.contributor.author | Korobenko, A. | - |
dc.contributor.author | Di Scalea, F. Lanza | - |
dc.contributor.author | Todd, M. D. | - |
dc.contributor.author | Taylor, S. G. | - |
dc.date.accessioned | 2016-11-10T07:11:48Z | - |
dc.date.available | 2016-11-10T07:11:48Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Journal of Applied Mechanics, Transactions ASME, 2015, v. 82, n. 9 | - |
dc.identifier.issn | 0021-8936 | - |
dc.identifier.uri | http://hdl.handle.net/10722/235952 | - |
dc.description.abstract | Copyright © 2015 by ASME.In this paper, we combine recent developments in modeling of fatigue-damage, isogeometric analysis (IGA) of thin-shell structures, and structural health monitoring (SHM) to develop a computational steering framework for fatigue-damage prediction in full-scale laminated composite structures. The main constituents of the proposed framework are described in detail, and the framework is deployed in the context of an actual fatigue test of a full-scale wind-turbine blade structure. The results indicate that using an advanced computational model informed by in situ SHM data leads to accurate prediction of the damage zone formation, damage progression, and eventual failure of the structure. Although the blade fatigue simulation was driven by test data obtained prior to the computation, the proposed computational steering framework may be deployed concurrently with structures undergoing fatigue loading. | - |
dc.language | eng | - |
dc.relation.ispartof | Journal of Applied Mechanics, Transactions ASME | - |
dc.subject | Kirchhoff-Love shells | - |
dc.subject | DDDAS | - |
dc.subject | digital twin | - |
dc.subject | fatigue damage | - |
dc.subject | IGA | - |
dc.title | Isogeometric Fatigue Damage Prediction in Large-Scale Composite Structures Driven by Dynamic Sensor Data | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1115/1.4030795 | - |
dc.identifier.scopus | eid_2-s2.0-84953888837 | - |
dc.identifier.volume | 82 | - |
dc.identifier.issue | 9 | - |
dc.identifier.spage | null | - |
dc.identifier.epage | null | - |
dc.identifier.eissn | 1528-9036 | - |
dc.identifier.isi | WOS:000359190800008 | - |
dc.identifier.issnl | 0021-8936 | - |