Nonlinear system identification of smart reinforced concrete structures under impact loads
DC Field | Value | Language |
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dc.contributor.author | Arsava, K. Sarp | - |
dc.contributor.author | Nam, Yunyoung | - |
dc.contributor.author | Kim, Yeesock | - |
dc.date.accessioned | 2021-08-11T17:24:10Z | - |
dc.date.available | 2021-08-11T17:24:10Z | - |
dc.date.issued | 2016-09 | - |
dc.identifier.issn | 1077-5463 | - |
dc.identifier.issn | 1741-2986 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/8816 | - |
dc.description.abstract | This paper proposes system identification models of smart concrete structures equipped with magnetorheological (MR) dampers under a variety of high impact loads. The proposed model was used to predict and analyze the highly nonlinear behavior of integrated structure-control systems subjected to impact loading. Highly nonlinear behavior of the integrated structure-MR damper was represented by a wavelet-based time delayed adaptive neuro-fuzzy inference system (W-TANFIS). To generate sets of input and output data for training and validating the proposed W-TANFIS models, experimental studies were performed on a smart reinforced concrete beam under a variety of impact loads. The impact forces and current signals on an MR damper were used as input signals for training the W-TANFIS to predict the acceleration, deflection, and strain responses. As a benchmark, an adaptive neuro-fuzzy inference system (ANFIS) was used. It was demonstrated that the proposed W-TANFIS framework is effective in anticipating the structural responses of the reinforced concrete beam-MR damper system subjected to impact loading. In addition, the comparison of the W-TANFIS and ANFIS models demonstrated that the W-TANFIS model has better performance over the ANFIS model. | - |
dc.format.extent | 25 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | SAGE Publications | - |
dc.title | Nonlinear system identification of smart reinforced concrete structures under impact loads | - |
dc.type | Article | - |
dc.publisher.location | 영국 | - |
dc.identifier.doi | 10.1177/1077546314563966 | - |
dc.identifier.scopusid | 2-s2.0-84982980886 | - |
dc.identifier.wosid | 000382436700010 | - |
dc.identifier.bibliographicCitation | JVC/Journal of Vibration and Control, v.22, no.16, pp 3576 - 3600 | - |
dc.citation.title | JVC/Journal of Vibration and Control | - |
dc.citation.volume | 22 | - |
dc.citation.number | 16 | - |
dc.citation.startPage | 3576 | - |
dc.citation.endPage | 3600 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Acoustics | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Mechanics | - |
dc.relation.journalWebOfScienceCategory | Acoustics | - |
dc.relation.journalWebOfScienceCategory | Engineering, Mechanical | - |
dc.relation.journalWebOfScienceCategory | Mechanics | - |
dc.subject.keywordPlus | ONLINE IDENTIFICATION | - |
dc.subject.keywordPlus | FUZZY | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordPlus | DAMPERS | - |
dc.subject.keywordAuthor | Impact load | - |
dc.subject.keywordAuthor | magnetorheological (MR) damper | - |
dc.subject.keywordAuthor | smart structures | - |
dc.subject.keywordAuthor | system identification | - |
dc.subject.keywordAuthor | wavelet-based time delayed adaptive neuro-fuzzy inference system (W-TANFIS) | - |
dc.subject.keywordAuthor | wavelet transform | - |
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