Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/88836
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electrical Engineering | - |
dc.creator | Lu, C | - |
dc.creator | Feng, YW | - |
dc.creator | Fei, CW | - |
dc.creator | Bu, SQ | - |
dc.date.accessioned | 2020-12-22T01:08:18Z | - |
dc.date.available | 2020-12-22T01:08:18Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/88836 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ | en_US |
dc.rights | The following publication C. Lu, Y. Feng, C. Fei and S. Bu, "Decomposed-Coordinated Framework With Enhanced Extremum Kriging for Multicomponent Dynamic Probabilistic Failure Analyses," in IEEE Access, vol. 7, pp. 163287-163300, 2019, doi: 10.1109/ACCESS.2019.2952358. is available at https://dx.doi.org/10.1109/ACCESS.2019.2952358 | en_US |
dc.subject | E2K-DCf | en_US |
dc.subject | Multicomponent structure | en_US |
dc.subject | Multiple population genetic algorithm | en_US |
dc.subject | Probabilistic failure | en_US |
dc.subject | Turbine blisk | en_US |
dc.title | Decomposed-coordinated framework with enhanced extremum kriging for multicomponent dynamic probabilistic failure analyses | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 163287 | - |
dc.identifier.epage | 163300 | - |
dc.identifier.volume | 7 | - |
dc.identifier.doi | 10.1109/ACCESS.2019.2952358 | - |
dcterms.abstract | For multicomponent structures enduring dynamic workloads coming from multi-physical fields, safety assessment is significant to guarantee the normal operation of entire structure system. In this paper, an enhanced extremum Kriging-based decomposed coordinated framework (E2K-DCF) is proposed to improve the dynamic probabilistic failure analyses of multicomponent structures. In this method, extremum Kriging model (EKM) is developed by introducing Kriging model into extremum response surface method (ERSM) to process the transient response problem and shorten computational burden in dynamic probabilistic failure analyses. Multiple population genetic algorithm (MPGA) is employed to solve maximum likelihood equation (MLE) and find the optimal hyperparameter theta in the EKM, which is promising to enhance approximate accuracy; decomposed-coordinated (DC) strategy is used to handle the coordinated relationship of multiple analytical objectives. To validate the proposed E2K-DCF, the probabilistic failure analysis of turbine blisk radial deformation is conducted by comparing with different methods within time domain [0 s, 215 s], considering fluid-thermal-structural interaction. It is revealed that the failure probability of blisk radial deformation is only 0.0022 when the allowable value is 2.5702 x 10(-3) m acquired from real world practice. Compared to the other approaches, this E2K-DCF has obvious advantages in fitting time and accuracy as well as simulation efficiency and accuracy. The results illustrate that the E2K-DCF is effective and applicable in dynamic probabilistic failure analysis. The efforts of this paper provide a novel viewpoint for the transient reliability evaluation of multicomponent structures, which is likely to enrich mechanical reliability theory. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE access, 2019, , v. 7, p. 163287-163300 | - |
dcterms.isPartOf | IEEE access | - |
dcterms.issued | 2019 | - |
dc.identifier.isi | WOS:000510228400001 | - |
dc.identifier.eissn | 2169-3536 | - |
dc.description.validate | 202012 bcrc | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Lu_Decomposed-Coordinated_Framework.pdf | 1.96 MB | Adobe PDF | View/Open |
Page views
50
Last Week
0
0
Last month
Citations as of May 19, 2024
Downloads
22
Citations as of May 19, 2024
SCOPUSTM
Citations
11
Citations as of May 17, 2024
WEB OF SCIENCETM
Citations
7
Citations as of May 16, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.