# An Established Theory of Digital Twin Model for Tunnel Construction Safety Assessment
###### Abstract  
In traditional construction safety assessment, it is difficult to describe the safety status of different construction stages. To solve this problem, this paper proposes a digital twin modeling theory for construction safety assessment. Firstly, this paper analyzes the requirements of a digital twin model. Secondly, the required information is collected by IoT. Finally, the DT model is established based on the collected information. This DT model analyzes the collected information by ML, which aims to conducting the assessments of construction safety. To verify this method, this paper analyzes the vault settlement during tunnel construction. The analysis results show that the DT model can predict the settlement value with high accuracy. Moreover, the safety state is assessed dynamically based on the settlement value by DT.  
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In recent years, with the progress of science and technology, many countries have begun to promote the development of building industrialization and construction information, and monitoring technology also has made significant progress. More and more engineering data can be collected during the construction of tunnels. The engineering data used effectively is beneficial in controlling the safety risk in the construction process. Due to the characteristics of real-time interaction and self-evolution, digital twin (DT) is considered as the best technology that can contain all the required information [5]. Therefore, this paper uses DT to integrate and display all the construction data. This paper proposes a safety risk assessment framework with the DT model; the core of the DT model is all kinds of engineering data. Through establishing a digital twin construction model, various data in the construction process are analyzed and processed by machine learning algorithms. This paper introduces DT into the field of safety assessment and uses the characteristics of DT to establish a safety assessment method that meets the dynamic characteristics of construction. The safety assessment results are more consistent with the actual situation of the project and can better provide a basis for safety management. The digital twin model is based on the newly collected data for analysis and prediction to obtain the latest construction safety assessment. In brief, this work makes the following contributions:  
* A construction safety assessment framework based on DT is proposed.
* The modeling accuracy of each construction element in the twin model is divided.
* A digital twin model including geometric, physical and knowledge dimensions is established. This model covers various elements of the construction project and provides a basis for various safety assessments.
* Taking tunnel structure safety evaluation as an example (vault settlement), the feasibility of this assessment method is verified.  
The rest of this paper is as follows: the second chapter is a literature review, which introduces the characteristics and development of safety management and DT. The third chapter is about the construction safety evaluation framework of the DT. The fourth chapter introduces the modeling contents, information collection methods and modeling process in turn, including the establishment accuracy analysis of the virtual model, the appropriate method of data collection by the Internet of things (IoT), and the specific establishment process of the DT model. The fifth chapter verifies the above theory and framework through an actual tunnel construction case. The sixth chapter discusses the contribution and inadequacy of the article. The seventh chapter makes a final summary and outlook for the above content.