Risk Assessment of a Tunnel Collapse in a Mountain Tunnel Based on the Attribute Synthetic Evaluation System

Wang, Benshuo; Li, Shucai; Zhang, Qian‐qing; Li, Liping; Zhang, Qian; Xu, Fei

doi:10.1061/9780784480038.025

Cited by 8 publications

(3 citation statements)

References 7 publications

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“…A comprehensive assignment method is adopted for the weight value of factors, which can satisfy both historical and practical data and reduce the possibility of interference by human factors. Wang [57] combined grey theory with cooperative non-linear theory to establish a grey-collaborative non-linear theoretical model for landslide time prediction. Chen et al [58] took the Yinsong Water Diversion Project as an example based on the monitoring data of 18 collapse accidents during tunnel construction.…”

Section: Prediction Of Collapse and Outburst And Water Inflowmentioning

confidence: 99%

A Review of Deep Learning Applications in Tunneling and Underground Engineering in China

Su,

Hu,

Yang

et al. 2024

Applied Sciences

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With the advent of the era of big data and information technology, deep learning (DL) has become a hot trend in the research field of artificial intelligence (AI). The use of deep learning methods for parameter inversion, disease identification, detection, surrounding rock classification, disaster prediction, and other tunnel engineering problems has also become a new trend in recent years, both domestically and internationally. This paper briefly introduces the development process of deep learning. By reviewing a number of published papers on the application of deep learning in tunnel engineering over the past 20 years, this paper discusses the intelligent application of deep learning algorithms in tunnel engineering, including collapse risk assessment, water inrush prediction, crack identification, structural stability evaluation, and seepage erosion in mountain tunnels, urban subway tunnels, and subsea tunnels. Finally, it explores the future challenges and development prospects of deep learning in tunnel engineering.

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Section: Prediction Of Collapse and Outburst And Water Inflowmentioning

confidence: 99%

A Review of Deep Learning Applications in Tunneling and Underground Engineering in China

Su,

Hu,

Yang

et al. 2024

Applied Sciences

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“…(1) Risk/hazard identification in the tunnel collapse In actual engineering, the tunneling collapse may be affected by many factors, which interact with each other. Many scholars (Qiao et al, 2020;Wang et al, 2016Wang et al, , 2020Zhang et al, 2020) have studied the risk factors of collapse and established a similar index system. Referring to previous researches, a total of 15 risk factors are selected, as shown in Table 1.…”

Section: Collapse Risk Assessment Based Statistical Datamentioning

confidence: 99%

A Multi-source Information Fusion Approach in Tunnel Collapse Risk Analysis based on Improved Dempster-Shafer Evidence Theory

Qiu

Huang

et al. 2021

Preprint

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The tunneling collapse is the main engineering hazard in the construction of the drilling-and-blasting method. The accurate assessment of the tunneling collapse risk has become a key issue in tunnel construction. As for assessing the tunneling collapse risk and providing basic risk controlling strategies, this research proposes a novel multi-source information fusion approach that combines Bayesian network (BN), cloud model (CM), support vector machine (SVM), Dempster-Shafer (D-S) evidence theory, and Monte Carlo (MC) simulation technique. Those methods (CM, BN, SVM) are used to analyze multi-source information (i.e. statistical data, physical sensors, and expert judgment provided by humans) respectively and construct basic probability assignments (BPAs) of input factors under different risk states. Then, these BPAs will be merged at the decision level to achieve an overall risk evaluation, using an improved D-S evidence theory. The MC technology is proposed to simulate the uncertainty and randomness of data. The novel approach has been successfully applied in the case of the Jinzhupa tunnel of the Pu-Yan Highway (Fujian, China). The results indicate that the developed new multi-source information fusion method is feasible for (a) Fusing multi-source information effectively from different models with a high-risk assessment accuracy of 98.1%; (b) Performing strong robustness to bias, which can achieve acceptable risk assessment accuracy even under a 20% bias; and (c) Exhibiting a more outstanding risk assessment performance (97.9% accuracy) than the single-information model (78.8% accuracy) under a high bias (20%). Since the proposed reliable risk analysis method can efficiently integrate multi-source information with conflicts, uncertainties, and bias, it provides an in-depth analysis of the tunnel collapse and the most critical risk factors, and then appropriate remedial measures can be taken at an early stage.

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“…With the development of economy and the increase of building quantity, the contradiction between urban sustainable development and urban land shortage gradually appears. In order to reduce the occupied area and improve the utilization rate of land, a large number of buildings have been developed into high-rise underground buildings [1][2][3] . With the increase of the depth and area of underground project, the requirement of waterproof technology and waterproof material for underground building waterproof project is higher and higher.…”

Section: Introductionmentioning

confidence: 99%

Research on Grouting Materials for Underground Construction Projects

Duan

Zhao

Qin

et al. 2021

MSF

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The engineering practice shows that the application of grouting technology to treat underground engineering has strong applicability and is one of the most commonly used technical means at present. Based on the underground engineering, this paper introduces the research achievements of grouting materials in recent years, including cement-based grouting materials, mixed grouting materials, anti-scouring grouting materials, and ultra-fine cement grouting materials. Current demand of grouting materials in underground engineering, there exists large dosage of cement, high content, high cost, serious environmental pollution problems, such as looking for alternatives or mixed with other raw materials for preparation of cementation material become the development trend, compared with the cement grouting material, chemical grouting material with higher performance, but in smaller projects within the scope of application. How to reduce the production cost of chemical grouting materials, simplify the production process, overcome the existing toxicity, reduce environmental pollution and improve the durability of solidified body has become the bottleneck of its popularization and application. Some achievements have been made in the modification of cement or chemical materials by nanometer components, but there is still a long way to go before the large-scale application of grouting engineering.

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Risk Assessment of a Tunnel Collapse in a Mountain Tunnel Based on the Attribute Synthetic Evaluation System

Cited by 8 publications

References 7 publications

A Review of Deep Learning Applications in Tunneling and Underground Engineering in China

A Review of Deep Learning Applications in Tunneling and Underground Engineering in China

A Multi-source Information Fusion Approach in Tunnel Collapse Risk Analysis based on Improved Dempster-Shafer Evidence Theory

Research on Grouting Materials for Underground Construction Projects

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