Fuzzy risk assessment of a deeply buried tunnel under incomplete information

Abstract

Risk assessment has always been an important part of safety risk research in tunnel and underground engineering. Owing to the characteristics of tunnel construction, to achieve an expected risk control effect, it is necessary to carry out accurate risk assessment research according to the risk assessment concept based on the entire tunnel construction process. At present, because of the frequent occurrences of safety accidents, a variety of risk assessment models have been proposed for different tunnel projects such as subways and railway tunnels, which can be roughly classified into two types: probability-based and fuzzy set theories. However, the existing models may be more suitable for the construction stage, and the design stage lacks a reliable and practical fuzzy risk assessment method. Therefore, based on fuzzy set theory and similarity measure theory, a risk assessment model is proposed to adapt to the characteristics that the risk information is difficult to quantify the fuzziness in the design phase. Firstly, new ideas of fuzzy risk analysis are proposed to overcome deficiencies in existing methods; secondly, a new similarity measure is constructed; then fusing multi-source fuzzy information based on evidence theory, the relationship between similarity measure and mass function is established. Finally, the new method is applied to the Yuelongmen tunnel. Results show that the concept of risk control and the risk assessment model are feasible.

Assessment of risks of tunneling project in Iran using artificial bee colony algorithm

“…They used fuzzy logic and similarity measure theory. The results clearly showed the capability of the proposed model for evaluating of risk this case study [29]. Li and Yang [30] used improved attribute mathematical theory to propose risk assessment model of tunnel water inrush.…”

“…Based on their results, they made some recommendations for a case study, railway tunnel engineering of the Yuelongmen tunnel in China [28]. A risk assessment model is proposed by Xia et al [29]. They used fuzzy logic and similarity measure theory.…”

Individual autonomous safety intelligence technology for radioactive material transportation—Multi-sensor fusion early warning technology based on evidence theory

“…Therefore, how to effectively address the handling of uncertain information in the fusion process is an urgent challenge to be solved. Information fusion technologies offer a variety of technical approaches, such as Bayesian theory [10], fuzzy set Theory [11], and D-S evidence theory [12,13].…”

Dynamic Risk-Warning of Center Diaphragm and Bench Composite Method During Construction

“…Therefore, scholars at home and abroad have carried out a lot of research on tunnel construction safety. There are many factors affecting construction safety and their contribution to risk value is different, so, in order to evaluate the construction safety scientifically and systematically, scholars like Wang et al [1] To solve the randomness and fuzziness of water inrush risk evaluation, a comprehensive evaluation model was established based on normal cloud theory; Yuan et al [2] established a Catastrophe theory model of tunnel collapse risk assessment based on the analysis of risk pregnancy environment and inducement of Hongyansi tunnel; Alireza et al [3] and others combined the game theory with the interactive decision structure model of the hierarchical process of fuzzy analysis for risk management in tunnel engineering design, construction and operation; Sousa et al [4] proposed a systematic approach to assess and manage tunnel constructionrelated risks based on Bayesian network; Ye et al [5] developed an intelligent risk assessment system for deep-base pit precipitation; Abdolreza [6] proposed a risk assessment model based on fuzzy set theory to assess risk events during tunnel construction; Bai et al [7] proposed a multi-stage risk management approach to better carry out risk management and optimize risk mitigation; Cagatay [8] selected event tree analysis method to analyze the operating risk of tunnel construction TBM (tunnel tunneling machine); Han et al [9] proposed a risk assessment method to evaluate the pre-existing circumferential cracks of shield tunnel in order to ensure the safety of deep-digging tunnel during construction; Xia et al [10] based on fuzzy set theory and similarity measurement theory, proposed a risk assessment model which is difficult to quantify fuzzy characteristics; Lin et al [11] applied the improved cloud model to tunnel construction risk assessment; Xue et al [12] rediction model for subway tunnel collapse risk based on Delphi-Ideal point method and geological forecast. Some scholars use monitoring techniques to predict the possibility of risk occurrence, scholars like Mahdi et al [13] combined monitoring with mathematical evaluation methods according to the safety impacts of subway construction on adjacent existing bridges, and established the safety risk assessment and control system of the existing bridges including four aspects: pre-work detection, pre-work assessment, in-work dynamic control, post-work evaluation and recovery; Su et al [14] used PSO-ANN model to predict the feasibility of surface settlement caused by tunnel excavation; Liu et al [15] introduced microseismic monitoring and risk management theory in tunnel blasting excavation, which can obtain the probability of occurrence, potential consequences and risk grade of rock burst in real time; Liu et al [16] proposed the reliability analysis of subway tunnel operation based on dy...…”