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Building demolition estimation in urban road widening projects using as-is BIM models

Jiang, Feng; Ma, Ling; Broyd, Tim; Chen, Ke; Luo, Hanbin; Du, Muzi; (2022) Building demolition estimation in urban road widening projects using as-is BIM models. Automation in Construction , 144 , Article 104601. 10.1016/j.autcon.2022.104601. Green open access

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Abstract

Building demolition caused by urban road widening projects can lead to engineering, economic, and environmental issues and should be planned at the design stage. Based on as-is BIM, this paper proposes a method to estimate the building demolition caused by urban road widening using online map data and statistics on government websites. The as-is BIM models of the existing old road and its surrounding buildings are created, and the BIM models of the newly widened road are built based on the as-is BIM models considering road components in accordance with road engineering expressions to assist building demolition estimation using clash detection. This paper presents a cost-effective building demolition estimation in urban road widening projects without field surveys. It was tested on the M4 Motorway project in London. It has been proved to be a very practical approach to facilitate urban road planning and decision making.

Type: Article
Title: Building demolition estimation in urban road widening projects using as-is BIM models
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.autcon.2022.104601
Publisher version: https://doi.org/10.1016/j.autcon.2022.104601
Language: English
Additional information: © 2022 The Author(s). Published by Elsevier B.V. under a Creative Commons license (https://creativecommons.org/licenses/by/4.0/).
Keywords: As-is BIM, Building information modelling (BIM), Road widening, Road engineering, Alignment fitting, Building demolition, Cost estimation
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10156971
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