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dc.contributor.authorAbrishami, S
dc.contributor.authorGoulding, J
dc.contributor.authorRahimian, F
dc.date.accessioned2020-08-25T08:20:08Z
dc.date.available2020-08-25T08:20:08Z
dc.date.issued2020-07-10
dc.identifier.citationAbrishami, S., Goulding, J. and Rahimian, F. (2020), Generative BIM workspace for AEC conceptual design automation: prototype development, Engineering, Construction and Architectural Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ECAM-04-2020-0256en
dc.identifier.issn0969-9988en
dc.identifier.doi10.1108/ECAM-04-2020-0256en
dc.identifier.urihttp://hdl.handle.net/2436/623510
dc.descriptionThis is an accepted manuscript of an article published by Emerald in Engineering, Construction and Architectural Management on 10/07/2020, available online: https://doi.org/10.1108/ECAM-04-2020-0256 The accepted version of the publication may differ from the final published version.en
dc.description.abstractPurpose: The integration and automation of the whole design and implementation process have become a pivotal factor in construction projects. Problems of process integration, particularly at the conceptual design stage, often manifest through a number of significant areas, from design representation, cognition and translation to process fragmentation and loss of design integrity. Whilst building information modelling (BIM) applications can be used to support design automation, particularly through the modelling, amendment and management stages, they do not explicitly provide whole design integration. This is a significant challenge. However, advances in generative design now offer significant potential for enhancing the design experience to mitigate this challenge. Design/methodology/approach: The approach outlined in this paper specifically addresses BIM deficiencies at the conceptual design stage, where the core drivers and indicators of BIM and generative design are identified and mapped into a generative BIM (G-BIM) framework and subsequently embedded into a G-BIM prototype. This actively engages generative design methods into a single dynamic BIM environment to support the early conceptual design process. The developed prototype followed the CIFE “horseshoe” methodology of aligning theoretical research with scientific methods to procure architecture, construction and engineering (AEC)-based solutions. This G-BIM prototype was also tested and validated through a focus group workshop engaging five AEC domain experts. Findings: The G-BIM prototype presents a valuable set of rubrics to support the conceptual design stage using generative design. It benefits from the advanced features of BIM tools in relation to illustration and collaboration (coupled with BIM's parametric change management features). Research limitations/implications: This prototype has been evaluated through multiple projects and scenarios. However, additional test data is needed to further improve system veracity using conventional and non-standard real-life design settings (and contexts). This will be reported in later works. Originality/value: Originality and value rest with addressing the shortcomings of previous research on automation during the design process. It also addresses novel computational issues relating to the implementation of generative design systems, where, for example, instead of engaging static and formal description of the domain concepts, G-BIM actively enhances the applicability of BIM during the early design stages to generate optimised (and more purposeful) design solutions.en
dc.formatapplication/pdfen
dc.languageen
dc.language.isoenen
dc.publisherEmeralden
dc.relation.urlhttps://www.emerald.com/insight/content/doi/10.1108/ECAM-04-2020-0256/full/htmlen
dc.subjectAIen
dc.subjectgenerative designen
dc.subjectgenetic algorithmen
dc.subjectspace syntaxen
dc.subjectconceptual designen
dc.titleGenerative BIM workspace for AEC conceptual design automation: prototype developmenten
dc.typeJournal articleen
dc.identifier.eissn1365-232X
dc.identifier.journalEngineering, Construction and Architectural Managementen
dc.date.updated2020-08-11T06:58:44Z
dc.date.accepted2020-06-08
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW21082020JGen
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2020-08-25en
dc.source.volume2020
dc.source.issueahead-of-print
dc.source.beginpage1
dc.description.versionPublished version
refterms.dateFCD2020-08-21T11:48:53Z
refterms.versionFCDAM
refterms.dateFOA2020-08-25T08:20:09Z


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