Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantita...Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.展开更多
Tunnel stability control is a world-wide difficult problem. For the sake of solving it,the new theory of soft rock engineering mechanics has been estabilished. Some key points,such as the definition and classification...Tunnel stability control is a world-wide difficult problem. For the sake of solving it,the new theory of soft rock engineering mechanics has been estabilished. Some key points,such as the definition and classification of soft rock, mechanical deformation mechanism of a soft rock tunnel, the critical support technique of soft rock tunnel and the new theory of the soft rock tunnel stability control are proposed in this paper.展开更多
In order to study the failure characteristics and control method of deep tunnel surrounding rock, based on the stress test, the structure and stress state of the main transportation tunnel surrounding rock in Mine Zha...In order to study the failure characteristics and control method of deep tunnel surrounding rock, based on the stress test, the structure and stress state of the main transportation tunnel surrounding rock in Mine Zhaogezhuang level 14 was analyzed, and it shows that the surrounding rock is exposed to an interphase hard and soft disadvantageous structure state and complex high stress repeated addition area;Through the theoretical analysis and the statistical data, the relation between the tunnel stress transformation and the surrounding rock deformation was proposed;Through the numerical simulation of the tunnel surrounding rock failure process with the help of RFPA procedure, the results show that the damage of the transportation tunnel level 14 mainly occurs in the bottom and the two coal ribs, and the failure process is spreading from the bottom to the two coal ribs, and the effect of the surrounding rock deformation control is obvious by using the way of 2.5 m anchor with 1.0 m grouting strengthening.展开更多
基金supported by the National Natural Science Foundation of China(Nos.52279107 and 52379106)the Qingdao Guoxin Jiaozhou Bay Second Submarine Tunnel Co.,Ltd.,the Academician and Expert Workstation of Yunnan Province(No.202205AF150015)the Science and Technology Innovation Project of YCIC Group Co.,Ltd.(No.YCIC-YF-2022-15)。
文摘Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.
文摘Tunnel stability control is a world-wide difficult problem. For the sake of solving it,the new theory of soft rock engineering mechanics has been estabilished. Some key points,such as the definition and classification of soft rock, mechanical deformation mechanism of a soft rock tunnel, the critical support technique of soft rock tunnel and the new theory of the soft rock tunnel stability control are proposed in this paper.
文摘In order to study the failure characteristics and control method of deep tunnel surrounding rock, based on the stress test, the structure and stress state of the main transportation tunnel surrounding rock in Mine Zhaogezhuang level 14 was analyzed, and it shows that the surrounding rock is exposed to an interphase hard and soft disadvantageous structure state and complex high stress repeated addition area;Through the theoretical analysis and the statistical data, the relation between the tunnel stress transformation and the surrounding rock deformation was proposed;Through the numerical simulation of the tunnel surrounding rock failure process with the help of RFPA procedure, the results show that the damage of the transportation tunnel level 14 mainly occurs in the bottom and the two coal ribs, and the failure process is spreading from the bottom to the two coal ribs, and the effect of the surrounding rock deformation control is obvious by using the way of 2.5 m anchor with 1.0 m grouting strengthening.
