Investigation of temperature effect on the optimal weight design of steel truss bridges using Cuckoo Search Algorithm

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In this article, the optimum weight design of steel truss bridges is carried out by considering the effect of temperature. One of the most significant issues such structures may encounter throughout their service life is the extreme temperature changes that can occur for various reasons. If a steel bridge is designed without considering this unfavorable scenario that might arise in the future, significant damage could happen in terms of the usability limit state, and it might even collapse by exceeding its carrying capacity before reaching its service life. Therefore, this study aims to conduct weight optimizations of steel truss bridges, considering the effect of temperature. Thus, it has been revealed how high-temperature variations alter material properties and affect the overall optimum weight of the structure. For this purpose, the minimum-weight designs of three planar steel truss bridges previously analyzed by other researchers have been re-evaluated using the Cuckoo Search Algorithm. The main program containing the flow steps of the algorithm based on the finite element method is coded in MATLAB. Stress and displacement limit values are used as constraints in solving the problems. The optimum weight results for each structure in the case of temperature effect not being considered are relatively similar. Thus, it has been demonstrated that the Cuckoo Search Algorithm can optimize such problems by comparing its results with similar studies in the literature. Then, the analyses are renewed by incorporating the temperature effect using this proven method. When the findings of both cases are examined, it is observed that the optimum weight values for all structures under the influence of temperature increase. This is due to the decrease in the material's modulus of elasticity because of the high-temperature change. In this case, the cross-section is insufficient owing to the loss of rigidity, and larger profiles are needed. The structure's weight tends to increase depending on the severity of the temperature. Also, numerical simulations of the structures under the same conditions are carried out with SAP2000 software to supplement the design optimization analyses detailed above and enrich the research content.

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dc.contributor.authorKeleş, Meryem
dc.contributor.authorArtar, Musa
dc.contributor.authorErgün, Mustafa
dc.date.accessioned2026-10-29T19:10:22.298647916Z
dc.date.available2026-10-29T19:10:22.298647916Z
dc.date.issued2024
dc.description.abstractIn this article, the optimum weight design of steel truss bridges is carried out by considering the effect of temperature. One of the most significant issues such structures may encounter throughout their service life is the extreme temperature changes that can occur for various reasons. If a steel bridge is designed without considering this unfavorable scenario that might arise in the future, significant damage could happen in terms of the usability limit state, and it might even collapse by exceeding its carrying capacity before reaching its service life. Therefore, this study aims to conduct weight optimizations of steel truss bridges, considering the effect of temperature. Thus, it has been revealed how high-temperature variations alter material properties and affect the overall optimum weight of the structure. For this purpose, the minimum-weight designs of three planar steel truss bridges previously analyzed by other researchers have been re-evaluated using the Cuckoo Search Algorithm. The main program containing the flow steps of the algorithm based on the finite element method is coded in MATLAB. Stress and displacement limit values are used as constraints in solving the problems. The optimum weight results for each structure in the case of temperature effect not being considered are relatively similar. Thus, it has been demonstrated that the Cuckoo Search Algorithm can optimize such problems by comparing its results with similar studies in the literature. Then, the analyses are renewed by incorporating the temperature effect using this proven method. When the findings of both cases are examined, it is observed that the optimum weight values for all structures under the influence of temperature increase. This is due to the decrease in the material's modulus of elasticity because of the high-temperature change. In this case, the cross-section is insufficient owing to the loss of rigidity, and larger profiles are needed. The structure's weight tends to increase depending on the severity of the temperature. Also, numerical simulations of the structures under the same conditions are carried out with SAP2000 software to supplement the design optimization analyses detailed above and enrich the research content.
dc.identifier.articlenumber105819
dc.identifier.doi10.1016/j.istruc.2023.105819
dc.identifier.issn2352-0124
dc.identifier.scopus2-s2.0-85181168539
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/bayburt/13025
dc.identifier.volume59
dc.identifier.wosWOS:001152498800001
dc.language.isoen
dc.publisherElsevier Ltd
dc.relation.ispartofStructures
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectCuckoo Search Algorithm
dc.subjectOptimum weight design
dc.subjectSteel truss bridges
dc.subjectTemperature effect
dc.subject.classificationEngineering, Civil
dc.subject.classificationEngineering
dc.subject.otherLearning algorithms
dc.subject.otherMATLAB
dc.subject.otherSteel bridges
dc.subject.otherTrusses
dc.subject.otherCuckoo search algorithms
dc.subject.otherEffects of temperature
dc.subject.otherExtreme temperatures
dc.subject.otherHighest temperature
dc.subject.otherITS Services
dc.subject.otherLimit state
dc.subject.otherOptimal weight designs
dc.subject.otherOptimum weight designs
dc.subject.otherSteel truss bridge
dc.subject.otherTemperature changes
dc.subject.otherTemperature
dc.titleInvestigation of temperature effect on the optimal weight design of steel truss bridges using Cuckoo Search Algorithm
dc.typeArticle
rdl.citation.openalex11
rdl.citation.scopus16
rdl.citation.wos13
rdl.oa.statusclosed
rdl.oa.statusgreen
rdl.oa.urlhttp://hdl.handle.net/20.500.12403/3434
rdl.scopus.quartileQ1
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)