Design Optimization of Building Exit Locations Based on Building Information Model and Ontology

Xuefeng Zhao, Lingli Huang, Zhe Sun (), Xiongtao Fan and Meng Zhang
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Xuefeng Zhao: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Lingli Huang: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Zhe Sun: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Xiongtao Fan: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
Meng Zhang: Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China

Sustainability, 2023, vol. 15, issue 17, 1-18

Abstract: There are usually multiple functional spaces that meet different usage needs on each building floor. The number of people in different functional spaces varies, resulting in an uneven distribution of people on each floors. When the building is subject to hazards, users inside buildings usually evacuate to safe areas through safety exits. Obviously, when the exit location is close to the crowded area, more people can be evacuated as quickly as possible. However, existing methods for optimizing exit locations of buildings mainly by shortening evacuation paths with limited considerations of the dynamic distributions of evacuees. Since the ontology has semantic description capability and reasonability. Therefore, the ontology is used to organize the design information related to the optimization of exit locations. The rules are further set to reason about the distribution of evacuees and the optimal exit location. Therefore, a design optimization method for exit locations based on BIM and ontology is proposed. Firstly, the ontology is developed to describe the information needed for design optimization. Then, the plan layout information is extracted from BIM as ontology instances. Next, based on the evacuation simulations, the exit location optimization strategies were created for the different distribution of evacuees, and the strategies were translated into SWRL rules. Finally, the ontology instance and SWRL rules are combined to reason about the exit location optimization strategies for specific projects. Therefore, this study provided the exit location optimization strategies to make the evacuation time shorter by considering the distribution of evacuees. The automation of exit location reasoning is further enhanced by using the constructed ontology to organize the design information and by transforming the optimization strategies into SWRL rules. The feasibility of the method was verified using several cases. By comparing the evacuation time of people under the exit location recommended by this method and the exit location designed by the shortest evacuation path, it is concluded that the method proposed in this paper takes into account the distribution of people in the plane and the evacuation time is shorter.

Keywords: building design optimization; exit location; BIM; ontology (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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