Abstract
This study presents a cloud model‐based approach for risk assessment of existing tunnels in tunneling construction environments where the cloud model provides a basis for uncertainty transformation between its qualitative concepts and quantitative expressions. An evaluation index system is established for risk assessment of existing tunnels based on the tunnel‐induced failure mechanism analysis. The assessment result is obtained through the correlation with the cloud model of each risk level. Risk assessment for existing Guangzhou‐Shenzhen‐Hong Kong Railway Tunnel in the tunneling environment of Shenzhen Metro Line 6 is shown in a case study. Comparisons between Fuzzy Analytic Hierarchy Process (FAHP) methods are further discussed according to results. The proposed evaluation method is verified to be more competitive as the fuzziness and randomness of uncertainties in the risk assessment system can be considered comprehensively. This method can serve as a decision‐making tool for other similar project risk assessment methods to increase the likelihood of a successful project in an uncertain environment.
Highlights
In the past few decades, many infrastructures, such as metro system, were constructed in congested megacities in China.e construction of some metro tunnels needs to be carried out above or near existing tunnels due to the limited underground space. e disturbance from the tunneling construction may affect the safety of the existing tunnel in such surrounding strata[1, 2]
Current comprehensive evaluation approaches can be grouped into the following three categories [4,5,6]: (1) approaches based on fuzzy mathematics theory, e.g., fuzzy analytic hierarchy process; (2) approaches based on probability and statistics theory, e.g., Bayesian networks; (3) approaches based on artificial intelligence, e.g., neural networks. e current construction equipment and technology have become more intelligent and digital than the past ones; construction data are difficult to collect in engineering practice as the contractors are unwilling to publish data to the public
In view of the advantages of the cloud model theory, we introduce it into the risk assessment of an existing tunnel in tunneling construction environments. e uncertainty relationship between evaluation index and risk level is established by cloud model theory
Summary
In the past few decades, many infrastructures, such as metro system, were constructed in congested megacities in China. E cloud model is a quantitative and qualitative uncertainty transformation model first proposed by Li et al [12] It has the capability of expressing fuzziness and randomness existing in human knowledge representation. E cloud model expresses the relationship between the assessment index value and the risk level by expectation (Ex), entropy (En), and hyperentropy (He). It reflects the uncertainty between the two in the form of the point membership function, and the mapping relationship between the evaluation index and attribute measure is one-to-many. In view of the advantages of the cloud model theory, we introduce it into the risk assessment of an existing tunnel in tunneling construction environments. E forward cloud generator is used to generate cloud drops of the given cloud numerical characters in this study
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