Abstract
A hybrid method consisting of bow‐tie‐Bayesian network (BT‐BN) analysis and fuzzy theory is proposed in this research, in order to support predictive analysis of settlement risk during shield tunnel excavation. We verified the method by running a probabilistic safety assessment (PSA) for a tunnel section in the Wuhan metro system. Firstly, we defined the “normal excavation phase” based on the fuzzy statistical test theory. We eliminated the noise records in the tunnel construction log and extracted the occurrence probability of facility failures from the denoised database. We then obtained the occurrence probability of environmental failures, operational errors, and multiple failures via aggregation of weighted expert opinions. The expert opinions were collected in the form of fuzzy numbers, including triangular numbers and trapezoidal numbers. Afterwards, we performed the BT‐BN analysis. We mapped the bow‐tie analysis to the Bayesian network and built a causal network PSA model consisting of 16 nodes. Causes of the excessive surface settlement and the resulting surface collapse were determined by bow‐tie analysis. The key nodes of accidents were determined by introducing three key measures into the Bayesian inference. Finally, we described the safety measures for the key nodes based on the PSA results. These safety measures were capable of reducing the failure occurrence probability (in one year) of excessive surface settlement by 66%, thus lowering the accident probability caused by excessive surface settlement.
Highlights
A hybrid method consisting of bow-tie-Bayesian network (BT-BN) analysis and fuzzy theory is proposed in this research, in order to support predictive analysis of settlement risk during shield tunnel excavation
We described the safety measures for the key nodes based on the probabilistic safety assessment (PSA) results. ese safety measures were capable of reducing the failure occurrence probability of excessive surface settlement by 66%, lowering the accident probability caused by excessive surface settlement
Is study aims to (1) clearly define the “normal excavation phase” of shield tunneling based on the fuzzy statistical test theory and extract the occurrence probability of facility failures from existing structured data; (2) in the absence of available data, determine the occurrence probability of environmental failure, operational error, and multiple failures by aggregating fuzzy numbers of expert opinion; (3) perform probabilistic safety assessment (PSA) of settlement failure in tunnel construction through bow-tie-Bayesian network (BT-BN) analysis; (4) identify the key nodes for excessive surface settlement-caused surface collapse; and (5) develop appropriate safety measures
Summary
In order to thoroughly study the safety risk of surface settlement, it is necessary to analyze in real time the uncertain information in the risk factors from multiple sources. Such uncertainty, including fuzziness and stochasticity, is ubiquitous and restricts the application of traditional methodologies such as empirical formula, simulation, and analytical modeling. Other methods based on artificial intelligence such as neural networks suffer from the memory effect because it is difficult to update the risk factors in real time when new information arises. Mapping BT to BN allows dynamic risk analysis, and the key factors of the system can be identified by calculating the posterior probability through the Bayes theorem. Since the conditional probability can be calculated via the Bayes theorem, the importance measure of PSA can be introduced [30], and BN can be fitted with these important measures very well to calculate the importance measures accurately and . erefore, the BTBN analysis can analyze surface collapse caused by excessive surface settlement in shield tunneling metro construction and use PSA to confirm the critical causes of accidents by adding the importance measures
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