Analysis of Risk in Building Life Cycle Coupling BIM-based Energy Simulation and Semantic Modeling. (2017)

• Record Type: Journal Article
• Authors: Pruvost, Hervé; Scherer, Raimar J.
• Is Part Of: Procedia engineering. Volume 196(2017)
• Page Start: 1106
• Page End: 1113
• Publication Date: 2017
• Subjects: Risk -- Building Information Modeling -- Decision Making -- Uncertainty -- Ontology; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2017.08.068
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: Building Information Modeling (BIM) is being increasingly accepted by the building industry as an innovative method for integrating many different data related to a building. Part of this data concerns performance metrics expressed among others in terms of cost, energy consumption or system reliability. Such performance values are the focus of project stakeholders who try to optimize them already in building design phase. These values are computed by simulation software that reuses a subpart of the BIM data as input. This provides a better view of building performances but less on threats and underperformances in the building life cycle. Moreover, despite the existence of different risk analysis methods, these are still quite difficult to integrate into a BIM design process. This research aims at closing this gap by first, integrating risk information as well as related uncertainty sources into the BIM process. Second, a method is developed for simulating uncertainty and computing risk metrics. Finally, the evaluation of risk levels is supported by the use of semantic web technologies through a risk ontology.