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dc.contributor.authorTiachacht, Samir
dc.contributor.authorKhatir, Samir
dc.contributor.authorCuong, Le Thanh
dc.contributor.authorRao, Ravipudi Venkata
dc.contributor.authorMirjalili, Seyedali
dc.contributor.authorWahab, Magd Abdel
dc.date.accessioned2021-03-28T23:52:10Z
dc.date.available2021-03-28T23:52:10Z
dc.date.issued2021
dc.identifier.issn0177-0667en_US
dc.identifier.doi10.1007/s00366-021-01378-8en_US
dc.identifier.urihttp://hdl.handle.net/10072/403465
dc.description.abstractIn this paper, damage detection, localization and quantification are performed using modal strain energy change ratio (MSEcr) as damage indicator combined with a new optimization technique, namely slime mould algorithm (SMA) developed in 2020. The SMA algorithm is employed to assess structural damage and monitor structural health. Two structures, including a laboratory beam and a bar planar truss are considered to study the effectiveness of the proposed approach. Another recent algorithm called marine predators algorithm (MPA) is also used for comparison purposes with SMA. The MSEcr is utilized in the first stage to predict the location of the damaged elements. Single and multiple damages cases are analysed based on different number of modes to study the sensitivity of the proposed indicator to the total number of modes considered in the analysis. Next, this indicator is used as an objective function in a second stage to solve the inverse problem using SMA and MPA for damage quantification of the elements identified in the first stage. Experimental validation is conducted using a 3D frame structure with four stories that have damaged components. It is demonstrated that the proposed approach, using MSEcr and SMA, provides superior results for the considered structures. The effectiveness of this technique is tested by introducing a white Gaussian noise with different levels, namely 2% and 4%. The results show that the provided approach can predict the location and level of damage with high accuracy after introducing the noise.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglishen_US
dc.publisherSpringeren_US
dc.relation.ispartofjournalEngineering with Computersen_US
dc.subject.fieldofresearchApplied Mathematicsen_US
dc.subject.fieldofresearchArtificial Intelligence and Image Processingen_US
dc.subject.fieldofresearchComputation Theory and Mathematicsen_US
dc.subject.fieldofresearchcode0102en_US
dc.subject.fieldofresearchcode0801en_US
dc.subject.fieldofresearchcode0802en_US
dc.subject.keywordsScience & Technologyen_US
dc.subject.keywordsComputer Science, Interdisciplinary Applicationsen_US
dc.subject.keywordsEngineering, Mechanicalen_US
dc.titleInverse problem for dynamic structural health monitoring based on slime mould algorithmen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dcterms.bibliographicCitationTiachacht, S; Khatir, S; Cuong, LT; Rao, RV; Mirjalili, S; Wahab, MA, Inverse problem for dynamic structural health monitoring based on slime mould algorithm, Engineering with Computers, 2021en_US
dc.date.updated2021-03-28T22:09:38Z
gro.description.notepublicThis publication has been entered in Griffith Research Online as an advanced online version.en_US
gro.hasfulltextNo Full Text
gro.griffith.authorMirjalili, Seyedali


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