Computational Building Information Modelling for construction waste management: Moving from rhetoric to reality

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• 作者：Weisheng Lu^a ; ^{wilsonlu@hku.hk} ; Chris Webster^b ; ^{cwebster@hku.hk} ; Ke Chen^a ; ^{leochen@connect.hku.hk} ; Xiaoling Zhang^c ; ^{xiaoling.zhang@cityu.edu.hk} ; Xi Chen^a ; ^{chenx90@hku.hk}
• 关键词：Building Information Modelling (BIM) ; Construction waste management (CWM) ; Computational design
• 刊名：Renewable and Sustainable Energy Reviews
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：68
• 期：part_P1
• 页码：587-595
• 全文大小：1265 K
• 卷排序：68

文摘

There is a lively debate on the application of Building Information Modelling (BIM) to construction waste management (CWM). BIM can be utilized as a less expensive, virtual, and computational environment to enable designers to ponder different design options, or contractors to evaluate different construction schemes, both with a view to minimizing construction waste generation. However, existing debate on this topic too frequently treats BIM as a cure-all silver bullet; without some major hurdles being adequately addressed, the applications of BIM will remain rhetorical. This paper aims to demystify BIM's computational application to CWM. Based on a critical literature review, a prototypical framework of a computational BIM for CWM is delineated, within which the two key prerequisites of ‘information readiness’ and ‘computational algorithms’ are highlighted. Then, the paper details the required information and how it can be organized in a standalone database or encapsulated in existing BIM for CWM. Learning from the historical development of data infrastructure in the field of BIM-based cost management, the process to develop the required information is likely to be tortuous but is unavoidable. The paper further explores computational BIM algorithms that can manipulate the information to facilitate decision-making for CWM. Finally, the operation of computational BIM is elaborated by relating it to various prevailing procurement models within which BIM applications are contextualized. Although the framework reported here has been substantially developed for experimental application, , it is not to be taken as an immediately applicable solution but rather as an illustration of the kind of platform on which future development of computational BIM for CWM can proceed in a more efficient and effective fashion.