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dc.contributor.authorMa, Wei
dc.contributor.authorWang, Xiangyu
dc.contributor.authorWang, Jun
dc.contributor.authorXiang, Xiaolei
dc.contributor.authorSun, Junbo
dc.date.accessioned2023-03-14T04:57:00Z
dc.date.available2023-03-14T04:57:00Z
dc.date.issued2021
dc.identifier.citationMa, W. and Wang, X. and Wang, J. and Xiang, X. and Sun, J. 2021. Generative design in building information modelling (Bim): Approaches and requirements. Sensors. 21 (16): ARTN 5439.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/90926
dc.identifier.doi10.3390/s21165439
dc.description.abstract

The integration of generative design (GD) and building information modelling (BIM), as a new technology consolidation, can facilitate the constructability of GD’s automatic design solu-tions, while improving BIM’s capability in the early design phase. Thus, there has been an increasing interest to study GD‐BIM, with current focuses mainly on exploring applications and investigating tools. However, there are a lack of studies regarding methodological relationships and skill requirement based on different development objectives or GD properties; thus, the threshold of developing GD‐BIM still seems high. This study conducts a critical review of current approaches for developing GD in BIM, and analyses methodological relationships, skill requirements, and improvement of GD‐ BIM development. Accordingly, novel perspectives of objective‐oriented, GD component‐based, and skill‐driven GD‐BIM development as well as reference guides are proposed. Finally, future research directions, challenges, and potential solutions are discussed. This research aims to guide de-signers in the building industry to properly determine approaches for developing GD‐BIM and in-spire researchers’ future studies.

dc.languageEnglish
dc.publisherMDPI
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/LP180100222
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectScience & Technology
dc.subjectPhysical Sciences
dc.subjectTechnology
dc.subjectChemistry, Analytical
dc.subjectEngineering, Electrical & Electronic
dc.subjectInstruments & Instrumentation
dc.subjectChemistry
dc.subjectEngineering
dc.subjectgenerative design
dc.subjectbuilding information modelling
dc.subjecttechnology integration
dc.subjectmethodological relationships
dc.subjectskill requirement and improvement
dc.subjectnovel development perspectives
dc.subjectDIGITAL WORKFLOWS
dc.subjectFRAMEWORK
dc.subjectARCHITECTURE
dc.subjectPERFORMANCE
dc.subjectCUSTOMIZATION
dc.subjectINTEGRATION
dc.subjectCOMPOSITE
dc.subjectbuilding information modelling
dc.subjectgenerative design
dc.subjectmethodological relationships
dc.subjectnovel development perspectives
dc.subjectskill requirement and improvement
dc.subjecttechnology integration
dc.subjectConstruction Industry
dc.subjectConstruction Industry
dc.titleGenerative design in building information modelling (Bim): Approaches and requirements
dc.typeJournal Article
dcterms.source.volume21
dcterms.source.number16
dcterms.source.issn1424-8220
dcterms.source.titleSensors
dc.date.updated2023-03-14T04:57:00Z
curtin.departmentSchool of Design and the Built Environment
curtin.accessStatusOpen access
curtin.facultyFaculty of Humanities
curtin.contributor.orcidWang, Xiangyu [0000-0001-8718-6941]
curtin.contributor.orcidWang, Jun [0000-0003-3384-4050]
curtin.contributor.researcheridWang, Xiangyu [B-6232-2013]
curtin.identifier.article-numberARTN 5439
dcterms.source.eissn1424-8220
curtin.contributor.scopusauthoridWang, Xiangyu [35323443600] [56021280800] [57193394615] [57196469993] [57200031213] [8945580300]
curtin.repositoryagreementV3


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