Construction Process Simulation Facing Digital Twin

With the development of digitization, informatization, and intelligence in the field of civil engineering, a large amount of data has been accumulated during the construction process, forming engineering big data. How to effectively analyze the construction process by mining the relationship between these data to improve the management efficiency will be an important research direction. Graphs have natural advantages in describing complex association relationships between data and are widely used in the analysis and mining of association relationships. Therefore, this paper will make full use of the relationship between construction data based on the graph database to establish a process simulation framework facing digital twin. This framework consists of three parts. Firstly, data collection from BIM models, surveillance videos, and IoT networks is stored in a graph database. Secondly, the graph database will be imported into a discrete event simulation model to automatedly simulate the future construction process with the results written back to the graph database. This DES model will make full use of this data and its relationships to obtain a more reasonable result. Process information obtained from this DES, such as schedule information, resource information, cost information, will be directly connected to the components. Thirdly, the as-planned process, as-built construction process, and graph database-based process analysis results will be dynamically displayed on the digital twin model to support real-time decision-making. A case study is demonstrated to verify the proposed framework’s validity and feasibility.