Bayesian prediction of tunnel convergence combining empirical model and relevance vector machine

Chang, Xiangyu; Wang, Hao; Zhang, Y. M.; Wang, Feiqiu; Li, Zhaozhong

doi:10.1016/j.measurement.2021.110621

Cited by 14 publications

(2 citation statements)

References 41 publications

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“…Moreover, in recent years, 3D laser scanning techniques have been applied widely in other tunneling and mining applications [33,34]. As convergence monitoring is a wellknown tunneling problem [35][36][37][38][39][40], the authors in [40] proved that data provided by a mobile LiDAR system can be used as an input for the method that automatically detects road tunnel luminaries.…”

Section: State Of the Artmentioning

confidence: 99%

A Method for Large Underground Structures Geometry Evaluation Based on Multivariate Parameterization and Multidimensional Analysis of Point Cloud Data

et al. 2022

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In underground mining, new workings (tunnels) are constructed by blasting or mechanical excavation. The blasting technique used in underground mines is supported by economic aspects, especially for deposits characterized by hard rocks. Unfortunately, the quality of the result may be different than expected in terms of the general geometry of work or the roughness of excavation surfaces. The blasting technique is also a source of vibrations that may affect other existing structures, affecting their stability. Therefore, it is of great importance to monitor both the quality of the new tunnels and changes in existing tunnels that may cause rockfall from the sidewalls and ceilings of both new and existing tunnels. The length of mining tunnels and support structures in underground mines is massive. Even if one would like to limit monitoring of tunnel geometry to those used every day for major technological processes such as transport, it is a vast amount of work. What is more, any stationary monitoring system is hard to utilize both due to everyday blasting procedures and mobile machine operation. The method proposed here is based on quick LiDAR/Terrestrial Laser Scanner measurements to obtain a cloud of points, which allows generating the spatial model of a mine’s geometry. Data processing procedures are proposed to extract several parameters describing the geometry of the tunnels. Firstly, the model is re-sampled to obtain its uniform structure. Next, a segmentation technique is applied to separate the cross sections with a specific resolution. Statistical parameters are selected to describe each cross section for final 1D feature analysis along the tunnel length. Such a set of parameters may serve as a basis for blasting evaluation, as well as long-term deformation monitoring. The methodology was tested and validated for the data obtained in a former gold and arsenic mine Zloty Stok, Poland.

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Section: State Of the Artmentioning

confidence: 99%

A Method for Large Underground Structures Geometry Evaluation Based on Multivariate Parameterization and Multidimensional Analysis of Point Cloud Data

et al. 2022

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“…In recent years, domestic and foreign scholars have studied the safety risk assessment methods for tunnel construction. For example, Chang Xiangyu et al [2] proposed a hybrid method, using BN and RVM to perform a probabilistic risk assessment of tunnel-related risks and probabilistic risk assessment of the damage caused by existing property; PADTUN was introduced and used by Vania Dimitrova et al [3]. It can help to make a pathological diagnosis and evaluation of the tunnel.…”

Section: Introductionmentioning

confidence: 99%

Overall Resilient Evaluation of Surrounding Rock of In-Service High-Speed Railway Tunnel Based on Information Fusion-Improved Fuzzy Matter-Element

Dong

et al. 2023

Sustainability

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Once the high-speed railway tunnel is put into use, its resilience will determine the possibility of permanent safety of the tunnel due to the closure of the structural space of the high-speed railway tunnel in service. Resilience theory is introduced into a risk analysis of operating high-speed rail tunnels to improve the ability to respond to risks in operating high-speed rail tunnels and to relieve the aging phenomenon caused by changes in the tunnel with time. First, an evaluation framework for the safety resilience of existing high-speed railway tunnels is constructed. Starting from the attributes of resilience such as resistance, adaptability, and resilience, and considering the characteristics of high-speed railway tunnels, protective measures, emergency management measures, and other factors, we fit the risk factors and probability of accident type of the high-speed railway tunnel and establish a tunnel safety resilience evaluation index system with 10 indexes. Secondly, the method of information fusion is used to combine subjective weighting and objective weighting. Then, the comprehensive weight of the evaluation index is obtained based on the principle of minimum discriminant information. Thirdly, the system resilience evaluation model based on the TOPSIS improved fuzzy matter-element is constructed to determine the classification criteria of resilience. On this basis, based on the temporal and spatial variability of the ductile tunnel, the concepts of ductile transition and ductile attenuation are introduced and the tunnel toughness optimization model is established to suppress the attenuation situation, enhance the transition ability, and then improve the system resilience level. On this basis, an optimal lifting scheme is obtained. Finally, taking Ai-Min tunnel of Ha-Mu high-speed railway as the engineering background, the flexibility of the resilience system is calculated, and the resilience grade (3) of the rock system surrounding the tunnel is obtained. Combined with the numerical model, improvement measures for specific tunnel facilities are proposed. The results show that the Ai-Min tunnel system has a general ability to resist external intrusion and prevent disasters, and the resilience level is general. It should focus on improving the resilience level of the transition index. The resilience evaluation results of the evaluation model are consistent with the actual situation of the project.

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An efficient Bayesian multi-model framework to analyze reliability of rock structures with limited investigation data

Kumar,

Tiwari

2023

Acta Geotech.

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Bayesian prediction of tunnel convergence combining empirical model and relevance vector machine

Cited by 14 publications

References 41 publications

A Method for Large Underground Structures Geometry Evaluation Based on Multivariate Parameterization and Multidimensional Analysis of Point Cloud Data

A Method for Large Underground Structures Geometry Evaluation Based on Multivariate Parameterization and Multidimensional Analysis of Point Cloud Data

Overall Resilient Evaluation of Surrounding Rock of In-Service High-Speed Railway Tunnel Based on Information Fusion-Improved Fuzzy Matter-Element

An efficient Bayesian multi-model framework to analyze reliability of rock structures with limited investigation data

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