Optimum design of braced steel frames via teaching learning based optimization
dc.authorid | 56652140200 | |
dc.contributor.author | Artar M. | |
dc.date.accessioned | 20.04.201910:49:12 | |
dc.date.accessioned | 2019-04-20T21:43:29Z | |
dc.date.available | 20.04.201910:49:12 | |
dc.date.available | 2019-04-20T21:43:29Z | |
dc.date.issued | 2016 | |
dc.department | Bayburt Üniversitesi | en_US |
dc.description.abstract | In this study, optimum structural designs of braced (non-swaying) planar steel frames are investigated by using one of the recent meta-heuristic search techniques, teaching-learning based optimization. Optimum design problems are performed according to American Institute of Steel Construction-Allowable Stress Design (AISCASD) specifications. A computer program is developed in MATLAB interacting with SAP2000 OAPI (Open Application Programming Interface) to conduct optimization procedures. Optimum cross sections are selected from a specified list of 128W profiles taken from AISC. Two different braced planar frames taken from literature are carried out for stress, geometric size, displacement and inter-storey drift constraints. It is concluded that teaching-learning based optimization presents robust and applicable optimum solutions in multi-element structural problems. © 2016 Techno-Press, Ltd. | en_US |
dc.identifier.doi | 10.12989/scs.2016.22.4.733 | |
dc.identifier.endpage | 744 | |
dc.identifier.issn | 1229-9367 | |
dc.identifier.issue | 4 | |
dc.identifier.scopus | 2-s2.0-85006515490 | en_US |
dc.identifier.scopusquality | Q1 | en_US |
dc.identifier.startpage | 733 | |
dc.identifier.uri | https://dx.doi.org/10.12989/scs.2016.22.4.733 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12403/574 | |
dc.identifier.volume | 22 | |
dc.identifier.wos | WOS:000391137400002 | en_US |
dc.identifier.wosquality | Q1 | en_US |
dc.indekslendigikaynak | Web of Science | en_US |
dc.indekslendigikaynak | Scopus | en_US |
dc.language.iso | en | en_US |
dc.publisher | Techno Press | |
dc.relation.ispartof | Steel and Composite Structures | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | MATLABSAP2000 OAPI | |
dc.subject | Optimum design | |
dc.subject | Planar steel frames | |
dc.subject | Teaching-learning based optimization | |
dc.subject | Application programming interfaces (API) | |
dc.subject | Application programs | |
dc.subject | Computer programming | |
dc.subject | Heuristic algorithms | |
dc.subject | MATLAB | |
dc.subject | Optimization | |
dc.subject | Steel construction | |
dc.subject | Structural design | |
dc.subject | Structural frames | |
dc.subject | American institute of steel constructions | |
dc.subject | MATLABSAP2000 OAPI | |
dc.subject | Meta-heuristic search techniques | |
dc.subject | Open application programming interface | |
dc.subject | Optimum designs | |
dc.subject | Optimum structural design | |
dc.subject | Planar steel frames | |
dc.subject | Teaching-learning-based optimizations | |
dc.subject | Structural optimization | |
dc.subject | MATLABSAP2000 OAPI | |
dc.subject | Optimum design | |
dc.subject | Planar steel frames | |
dc.subject | Teaching-learning based optimization | |
dc.subject | Application programming interfaces (API) | |
dc.subject | Application programs | |
dc.subject | Computer programming | |
dc.subject | Heuristic algorithms | |
dc.subject | MATLAB | |
dc.subject | Optimization | |
dc.subject | Steel construction | |
dc.subject | Structural design | |
dc.subject | Structural frames | |
dc.subject | American institute of steel constructions | |
dc.subject | MATLABSAP2000 OAPI | |
dc.subject | Meta-heuristic search techniques | |
dc.subject | Open application programming interface | |
dc.subject | Optimum designs | |
dc.subject | Optimum structural design | |
dc.subject | Planar steel frames | |
dc.subject | Teaching-learning-based optimizations | |
dc.subject | Structural optimization | |
dc.title | Optimum design of braced steel frames via teaching learning based optimization | en_US |
dc.type | Article | en_US |