A Bim-Based Identification and Classification Method of Environmental Risks in the Design of Beijing Subway

Abstract

The subway project safety risk management in China covers design and construction stages. The traditional method for identifying construction safety risks at the design stage requires that engineers work backward, and it relies on engineers having an accurate understanding of complex engineering information, spatial relationships, and rich experience. This paper proposes a Building Information Modeling (BIM) based automatic identification and classification framework for environmental risks at the subway design stage. First, a database of discriminant rules was established in order to achieve the digital expression of the discriminant standards for environmental risks. Second, environmental models and discriminant models were created in order to analyze spatial collisions. Then, the risk discrimination algorithm was embedded in the BIM platform. The program automatically analyzed the collision result-based discrimination rule database and output a list of environmental risks associated with the model. Finally, a shield tunnel was used for practice. As a result, the BIM-based method for automatically identifying environmental risks could improve the efficiency of the special design of safety risks and promote the digital transmission of risk design information throughout the construction process. The method described in this paper provides a reference for the safety risk management technology system in China’s subway projects. This method can also be applied to projects such as underground pipe gallery, power tunnel, and foundation pit, after optimizing the classification rules.

Intelligent Risk Management in Construction Projects: Systematic Literature Review

“…In order to reduce communication between project participants, (S. Zhang et al, 2017) [30] suggested the use of a BIM platform on which they could collaborate and manage the project. [14] integrates BIM platform technology with IoT technology to provide online, real-time exchange of information and personalization of products for assembled buildings. Nevertheless, few studies have incorporated BIM platforms with knowledge mapping technology and risk analysis models for dynamic and real-time intelligent risk management.…”

“…This cluster addressed the use of BIM in risk management. Accordingly, [79] designed an automatic identification and classification of environmental risks within a design phase BIM system, integrated risk management with an integrated BIM platform, and validated the risk management platform with the help of a specific project. An approach based on BIM that would identify environmental risks automatically and would facilitate the transfer of information regarding risk during construction in addition to increasing the efficiency of safety risk-specific design.…”

“…The majority of risk evaluations make use of probabilistic calculations and mathematical statistics based on small samples, which are suitable for the analysis of risk sources, accident hazards, and risk evaluations of single-dimensional scenarios, but are insufficient for the analysis of an enormous amount of information and data in a multi-dimensional scenario [13]. Currently available risk warning methods are mostly based on single indicators of risk source state parameters, risk development consequence prediction, and causality modelling between risks, but rarely take into account correlations of various risk factors in building information, and the data rate is insufficient [14].…”

Dealing with uncertainties in the design phase of road projects

“…Qazi et al (2020) said that interdependency modelling of uncertainty had been discussed using different qualitative and quantitative techniques. These models were based on the interpretive ranking process and system dynamics (Mhatre et al, 2017), Artifitial Intelligence (AI) (Afzal et al, 2021), fuzzy system (Valipour et al, 2015), meta-network analysis (Wang et al, 2021), Building Information Modelling (BIM) (Zhou et al, 2021) and multi-criteria decision-making model (Albogamy and Dawood, 2015;Burcar Dunovic et al, 2016). All these models were used to forecast the influence of uncertainties on project objectives.…”

“…, 2015), meta-network analysis (Wang et al. , 2021), Building Information Modelling (BIM) (Zhou et al. , 2021) and multi-criteria decision-making model (Albogamy and Dawood, 2015; Burcar Dunovic et al.…”