Numerical modeling for rockbursts: A state-of-the-art review

Wang, Jun; Apel, Derek B.; Pu, Yuanyuan; Hall, Robert A.; Wei, Chenyu; Sepehri, Mohammadali

doi:10.1016/j.jrmge.2020.09.011

Cited by 64 publications

(28 citation statements)

References 79 publications

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“…Numerous technologies have been put forward to evaluate rockburst in the last few decades. These methods include empirical methods, numerical simulation, experimental methods, and intelligent algorithms 3 , 9 , 10 .…”

Section: Introductionmentioning

confidence: 99%

“…The empirical method has a narrow scope of application 18 . Numerical simulation for rockburst prediction has high requirements on simulation methods, mechanical constitutive model, and rockburst mechanism 10 . The rock mechanics test for evaluating rockburst requires samples preparation and adequate types of equipment 19 , which is expensive and time consuming.…”

Section: Introductionmentioning

confidence: 99%

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Novel ensemble intelligence methodologies for rockburst assessment in complex and variable environments

Liu

Armaghani

et al. 2022

Sci Rep

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Rockburst is a severe geological hazard that restricts deep mine operations and tunnel constructions. To overcome the shortcomings of widely used algorithms in rockburst prediction, this study investigates the ensemble trees, i.e., random forest (RF), extremely randomized tree (ET), adaptive boosting machine (AdaBoost), gradient boosting machine, extreme gradient boosting machine (XGBoost), light gradient boosting machine, and category gradient boosting machine, for rockburst estimation based on 314 real rockburst cases. Additionally, Bayesian optimization is utilized to optimize these ensemble trees. To improve performance, three combination strategies, voting, bagging, and stacking, are adopted to combine multiple models according to training accuracy. ET and XGBoost receive the best capabilities (85.71% testing accuracy) in single models, and except for AdaBoost, six ensemble trees have high accuracy and can effectively foretell strong rockburst to prevent large-scale underground disasters. The combination models generated by voting, bagging, and stacking perform better than single models, and the voting 2 model that combines XGBoost, ET, and RF with simple soft voting, is the most outstanding (88.89% testing accuracy). The performed sensitivity analysis confirms that the voting 2 model has better robustness than single models and has remarkable adaptation and superiority when input parameters vary or miss, and it has more power to deal with complex and variable engineering environments. Eventually, the rockburst cases in Sanshandao Gold Mine, China, were investigated, and these data verify the practicability of voting 2 in field rockburst prediction.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Novel ensemble intelligence methodologies for rockburst assessment in complex and variable environments

Liu

Armaghani

et al. 2022

Sci Rep

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“…To guide the prevention and control of rock burst, Lai et al divided the roof failure period into three stages in which the accelerated active stage was the hazard preparation stage [13]. e numerical modeling method was used by Wang et al to study the mechanisms and the prediction of rock bursts, which provides some references and guidelines for preventing and mitigating rock bursts in underground mines [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of Prevention and Control of Rock Burst in Steeply Inclined Coal Seams by Mining Sequence and Filling

Zhang

Liu

Zhu

et al. 2022

Shock and Vibration

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The control and prevention of rock burst in a steeply inclined coal seam are essential. In order to figure out the effects of filling and mining sequence on rock burst in the steeply inclined coal seam, B3+6 and B1+2 coal seams in Wudong coal mine are chosen as the research objects, and an in-house experiment system of similarity simulation is established in this study. Combined with numerical simulation, the characteristics of collapse, stress distribution, and displacement variations can be measured, which provide useful information to study the effects of the filling body and mining sequence on rock burst. Experimental results show that the key reason for rock burst in a steeply inclined coal seam is the stress concentration of the rock pillar between B3+6 and B1+2 coal seams instead of the stress-lever-effect of a deeper rock pillar. The filling body can support the middle rock pillar, share the geological structure stress in the horizontal and vertical direction, eliminate the stress concentration zone largely, and prevent the occurrence of rock burst. When multiple working faces are working, the opposite side of the coal seam should be mined first to release the energy in the rock in advance, thus preventing the rock burst effectively. The research results provide fundamental information for better understanding the reason for rock burst and preventing rock burst in the steeply inclined coal seam.

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“…Due to the exploitation of deposits prone to spontaneous combustion, filling a selected space with cemented paste backfill creates favorable conditions because the hardened filling provides good isolation of the goafs and their access to fresh air, which prevents the formation of favorable conditions for the formation of endogenous fires [6]. Additionally, various types of backfills are used in the rock mass, which is prone to the release of seismic energy in the form of tremors and rock bursts [7]. For shallow deposits, the hardened backfill protects against surface subsidence, preventing the loosening of overlying layers, which is of great importance in creating safe operating conditions, especially under water reservoirs, important objects of ground infrastructure [8].…”

Section: Introductionmentioning

confidence: 99%

3D Numerical Modelling of the Application of Cemented Paste Backfill on Displacements around Strip Excavations

Skrzypkowski

2021

Energies

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This article presents laboratory and spatial numerical modeling of cemented paste backfill. The first part of the research concerned laboratory tests of a mixture of sand, water, and variable cement content (5%, 10%, and 15%). The density and curing time of the mixture were determined. Moreover, cylindrical samples with a diameter of 46 mm and a height of 92 mm were constructed, for which compressive and tensile strength were calculated after one, two, three, and four weeks. The second part of the research concerned 3D numerical modeling with the use of RS3 software. For the exploitation field with dimensions of 65 m × 65 m, a strip-mining method was designed. The main objective of the research was to determine the changes in displacements around the haulage room and transportation roadway located in the immediate vicinity of the exploitation field. For the first time in numerical modeling, a two-sided strip method was used for the four stages of mining the ore deposit where the post-mining space was filled with a cemented paste backfill. Based on this research, the compressibility coefficient was determined.

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Numerical modeling for rockbursts: A state-of-the-art review

Cited by 64 publications

References 79 publications

Novel ensemble intelligence methodologies for rockburst assessment in complex and variable environments

Novel ensemble intelligence methodologies for rockburst assessment in complex and variable environments

Experimental Study of Prevention and Control of Rock Burst in Steeply Inclined Coal Seams by Mining Sequence and Filling

3D Numerical Modelling of the Application of Cemented Paste Backfill on Displacements around Strip Excavations

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