概率逻辑
生命周期评估
天花板(云)
服务(商务)
使用寿命
可靠性(半导体)
不确定度分析
可靠性工程
工程类
运筹学
建筑工程
计算机科学
生产(经济)
模拟
业务
经济
宏观经济学
人工智能
营销
功率(物理)
物理
结构工程
量子力学
作者
Kyriaki Goulouti,Pierryves Padey,Alina Galimshina,Guillaume Habert,Sébastien Lasvaux
标识
DOI:10.1016/j.buildenv.2020.106904
摘要
The existing methods of evaluating the environmental life cycle assessment (LCA) and life cycle costs (LCC) performance of a building concept have been widely used, since they offer the possibility to consider the system globally and avoid, thus, the hidden impacts. However, many studies have indicated the possible uncertainties of the input parameters and recommended the use of probabilistic methods, to deal with these issues. The current study continues towards this direction and presents a systematic way to take into account the uncertainties of the building elements’ service life within a stochastic framework, by defining the corresponding probability density functions, based on a new service life database. Applying this methodology for the calculation of the LCA & LCC for multifamily houses in Switzerland revealed that the replacement stage contributes with a share of up to 36% on the GHG emissions. Furthermore, through a global sensitivity analysis, the uncertainty on the replacement rate of six building elements was found to mainly influence the LCA & LCC uncertainty, i.e. compact façade (external insulation), windows, roofing, flooring, internal layout and ceiling covering. Finally, it was found that the reference service life of the building significantly influences the LCA and LCC uncertainty. In order to increase the reliability on the building LCA and LCC results, it is recommended to take into account probabilistically the service lives of the building elements, which mostly influence the LCA uncertainty.
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