Abstract
Safety risk identification throughout deep excavation construction is an information-intensive task, involving construction information scattered in project planning documentation and dynamic information obtained from different field sensors. However, inefficient information integration and exchange have been an important obstacle to the development of automatic safety risk identification in actual applications. This research aims to achieve the requirements for information integration and exchange by developing a semantic industry foundation classes (IFC) data model based on a central database of Building Information Modeling (BIM) in dynamic deep excavation process. Construction information required for risk identification in dynamic deep excavation is analyzed. The relationships among construction information are identified based on the semantic IFC data model, involved relationships (i.e., logical relationships and constraints among risk events, risk factors, construction parameters, and construction phases), and BIM elements. Furthermore, an automatic safety risk identification approach is presented based on the semantic data model, and it is tested through a construction risk identification prototype established under the BIM environment. Results illustrate the effectiveness of the BIM-based central database in accelerating automatic safety risk identification by linking BIM elements and required construction information corresponding to the dynamic construction process.
Highlights
An industry foundation classes (IFC) data model-based approach is proposed in this research to realize automatic safety risk identification focusing on the entire deep excavation process, which can be divided into five steps
This research presents the development of a Building Information Modeling (BIM)-based central database, which aims to enable information integration and exchange between the dynamic deep excavation process and construction information in project planning documentation to support automatic safety risk identification
The effectiveness of the BIM-based central database in accelerating automatic safety risk identification is illustrated by linking BIM elements and required construction information corresponding to the dynamic construction process
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. With the development of information technology in the architecture, engineering, and construction (AEC) industries, building information modeling (BIM) with rich information has facilitated the acceleration of high-quality construction projects [8] In this context, limited risk identification-related assisting platforms that adopt building information models have been studied [7,9]. Information integration and exchange for safety risk identification of deep excavation are explored in this research to address the above research gap by using a BIM-based central database linking the dynamic construction process and risk-related information in project planning. This research aims to achieve the requirements for information integration and exchange by developing a semantic industry foundation classes (IFC) data model based on a central database of Building Information Modeling (BIM) in the dynamic deep excavation process. It is hoped that this study can provide a guidance for automatic risk identification in construction management
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