A framework using BIM and digital twins in facilitating LCSA for buildings
A framework using BIM and digital twins in facilitating LCSA for buildings
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DOI：
10.1016/j.jobe.2023.107232
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发表时间：
2023-07
影响因子：
6.4
通讯作者：
Calin Boje;Álvaro José Hahn Menacho;A. Marvuglia;E. Benetto;S. Kubicki;T. Schaubroeck;Tomás Navarrete Gutiérrez
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文献类型：
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作者：
Calin Boje;Álvaro José Hahn Menacho;A. Marvuglia;E. Benetto;S. Kubicki;T. Schaubroeck;Tomás Navarrete Gutiérrez
建筑业每年产生的二氧化碳排放量占全球的40%，除其他环境和社会影响外，它还为整个经济和社会发展做出了贡献。生命周期可持续性评估（LCSA）是一种经过验证的方法，用于评估产品系统在其生命周期内的环境，社会和经济影响。将LCSA应用于建筑领域并不简单，因为它需要收集和连接多个领域的数据。一个明显的研究差距是缺乏数据整合和完整性，无法进行地方性自我评估。本文解决了这一差距，并展示了如何互补使用建筑信息建模（BIM）和数字孪生（DT）源数据可以促进和改善建筑物的LCSA。它包括对当前最先进技术的回顾;提出了一种基于现有标准的新方法框架，并强调了BIM和DT在建筑环境中进行LCSA的作用;这在真实的办公楼的案例研究中进行了测试。研究结果表明，通常被忽视的社会影响可以考虑纳入LCSA，BIM和DT数据提供了更好的影响估计，这是必要的，以评估设计估计的影响和测量的性能之间的差距。实施这样一个框架的挑战，以及现有技术的局限性也突出和讨论。
The building and construction industry generates 40% of annual global CO2 emissions, aside from other environmental and social impacts, while it contributes to economic and societal development as a whole. Life Cycle Sustainability Assessment (LCSA) is a proven methodology to assess the environmental, social and economic impacts of a product system over its lifecycle. Applying LCSA to the construction domain is not trivial, as it needs to gather and connect data across several fields. A clear research gap was identified in the lack of data integration and completeness to carry out LCSA. This paper addresses this gap and shows how the complementary use of Building Information Modelling (BIM) and Digital Twin (DT) sourced data can facilitate and improve the LCSA of buildings. It includes a review of the current state of the art; proposes a novel methodological framework based on existing standards, and emphasises the roles of BIM and DT for conducting LCSA in the building context; this is tested in a case study of a real office building. The outcomes of the study demonstrate that the inclusion of usually neglected social impacts can be considered under LCSA, and that BIM and DT data provides better impact estimates, which are necessary to evaluate the performance gap between design estimated impacts and measured ones. The challenges of implementing such a framework, as well as the limitations of existing technologies are also highlighted and discussed.