Was ist ein Gebirgsschlag?

Dietz, Melanie M.; Oremek, G. M.; Groneberg, David A.; Bendels, M. H. K.

doi:10.1007/s40664-017-0215-z

Cited by 13 publications

(2 citation statements)

References 4 publications

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“…Rockburst occurs as a result of overstressing the rock mass or intact brittle rock, when the stresses exceed the compressive strength of the material [1,[8][9][10][11][12]. Rockburst can also be defined as sudden and intense movement, accompanied by rock failure, in underground spaces under high-stress conditions [1,[13][14][15][16]. Given the fact that Rockburst mechanisms and their predictions have been under serious research over the years, and have achieved thoughtful and profound results, as shown by the works produced by several authors.…”

Section: Introductionmentioning

confidence: 99%

A Decision Tree for Rockburst Conditions Prediction

et al. 2023

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This paper presents an alternative approach to predict rockburst using Machine Learning (ML) algorithms. The study used the Decision Tree (DT) algorithm and implemented two approaches: (1) using DT model for each rock type (DT-RT), and (2) developing a single DT model (Unique-DT) for all rock types. A dataset containing 210 records was collected. Training and testing were performed on this dataset with 5 input variables, which are: Rock Type, Depth, Brittle Index (BI), Stress Index (SI), and Elastic Energy Index (EEI). Other ML algorithms, such as Random Forest (RF), Support Vector Machine (SVM), Artificial Neural Network (ANN), K-Nearest Neighbor (KNN), and Gradient-Boosting (AdaboostM1), were implemented as a form of comparison to the DT models developed. The evaluation metrics and relative importance were utilized to examine some characteristics of the DT methods. The Unique-DT model showed a promising result of the two DT models, giving an average of (F1 = 0.65) in rockburst condition prediction. Although RF and AdaboostM1 (F1 = 0.66) performed slightly better, Unique-DT is recommended for predicting rockburst conditions because it is easier, more effective, and more accurate.

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Section: Introductionmentioning

confidence: 99%

A Decision Tree for Rockburst Conditions Prediction

et al. 2023

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“…From 1980 to 2009, all rockburst definitions focused on the ejection of rock mass when the rock energy is released [4][5][6][7]. Dietz et al [8] defined rockburst as a sudden and violent movement of rock in high-stress environments. In general, rockburst is a phenomenon in which the elastic energy accumulated in brittle and hard rock masses is disrupted by excavation due to the influence of high geostress.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation Analysis Method for Rockburst Control in Deeply Buried Caverns

Zhan,

Liu,

Xiao

et al. 2023

Applied Sciences

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Investigating the mechanism and measures of controlling rockburst in deeply buried underground caverns is a prerequisite for ensuring the safety of personnel, reducing the damage to construction equipment caused by the rockburst, and making the project economical and efficient. Efficient analysis methods for evaluating rockburst control in underground caverns are crucial for qualitatively selecting rockburst control methods and quantifying the effectiveness of rockburst measures. Based on the mechanism of energy accumulation in rock mass and the occurrence of rockburst as well as the active methods for controlling rockburst, we propose a mathematical model for simulating borehole stress relief using implicit borehole elements. In this modeling approach, we combine vector superposition in different borehole directions to analyze the effect of borehole stress relief on improving the external environment of the rock mass. Based on the interaction between the anchor support and the surrounding rock as well as the implementation of passive rockburst control measures, we propose a mathematical model that utilizes the implicit anchor column elements to simulate the reinforcement of the surrounding rock with anchors. By combining system anchors into arches and suspending anchors to reinforce the caverns, the overall stiffness of the surrounding rock can be improved and the stress accumulation can be alleviated. The coordinated deformation between the surrounding rock and the anchor provides support to prevent the rockburst. The effects of two rockburst control measures, borehole releasement and anchor reinforcement, are analyzed using both the strength theory and the energy theory. Engineering examples are provided to illustrate that the use of borehole elements to simulate local stress relief can effectively improve the external environment of the rock mass to control the occurrence of rockburst. Additionally, the mechanism of using anchor column elements in combination with the surrounding rock elements to enhance the overall stiffness of the rock mass and prevent rockburst is explored.

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