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Shear properties of cemented rockfills

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Journal of Rock Mechanics and Geotechnical Engineering 2018年第4期10卷 635-644页

作者： bob A.Lingga derek b.apel Department of Civil and Environmental Engineering School of Mining and Petroleum University of Alberta

Application of cemented rockfilling to underground mining could not be separated from the corresponding backfill’s shear strength properties. The shear of cemented rockfill(CRF)-rock wall and the shear interaction occurring within CRFs both have some disadvantageous failure chances. In this study,we tried to investigate the complete shear properties of CRFs using direct shear and triaxial tests of cemented granite rockfill. Large-scale triaxial testing was held to accommodate the large CRF *** shear testing on the prepared flat and smooth surfaces was assessed with brief conversions and their corrections were used to approximate the shear strength envelopes of CRF joint interfaces. Two types of CRFs with the same aggregate size and distribution but different unconfined compressive strengths(UCSs) due to different mixture designs indicated insignificant differences between their basic friction angles, and also their asperity inclination angles. Nevertheless, investigation between direct shear test and triaxial test showed that the specimen with higher UCS tended to have a slightly lower friction angle but a higher cohesion than the other one.

关键词： Cemented rockfill (CRF) Shear tests Shear strength Friction angle Cohesion backfill interface

Performance evaluation of near real-time condition monitoring in haul trucks

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International Journal of Mining Science and Technology 2020年第6期30卷 909-915页

作者： Hemanth Reddy Alla Robert Hall derek b.apel University of Alberta Edmonton T6G 2H5Canada

Strategic maintenance plays a key role in ensuring high availability and utilization of the haul trucks,and as equipment began to grow more complex towards the end of the 20th century,there was a need for a proactive maintenance strategy,which led to the development of condition-based *** condition monitoring(RTCM)is the ability to perform condition monitoring in real-time and has the ability to alert maintenance and operations of abnormal *** alarms can be used as an indication leading to a problem,and if a suitable corrective action is initiated in time,it could result in significant savings of equipment downtime and repair *** study aims to compare some maintenance performance indicators prior to and after implementation of RTCM strategy at a mine site using some tests of statistical *** study also indicated the presence of seasonality in the data,and thus the data was deseasonalized and detrended prior to being subjected to the statistical ***,the results indicated that RTCM strategy has proven to be successful in improving the availability for some of the failure categories chosen in this study.

关键词： Haul trucks Real-time condition monitoring Performance indicators

Machine learning methods for rockburst prediction-state-of-the-art review

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International Journal of Mining Science and Technology 2019年第4期29卷 565-570页

作者： Yuanyuan Pu derek b.apel Victor Liu Hani Mitri School of Mining and Petroleum Engineering University of AlbertaEdmonton T6G 2R3Canada Department of Mining and Materials Engineering McGill UniversityMontreal H3A 2T6Canada

One of the most serious mining disasters in underground mines is rockburst *** can lead to injuries and even fatalities as well as damage to underground openings and mining *** has forced many researchers to investigate alternative methods to predict the potential for rockburst ***,due to the highly complex relation between geological,mechanical and geometric parameters of the mining environment,the traditional mechanics-based prediction methods do not always yield precise *** the emergence of machine learning methods,a breakthrough in the prediction of rockburst occurrence has become possible in recent *** paper presents a state-ofthe-art review of various applications of machine learning methods for the prediction of rockburst ***,existing rockburst prediction methods are introduced,and the limitations of such methods are highlighted.A brief overview of typical machine learning methods and their main features as predictive tools is then *** current applications of machine learning models in rockburst prediction are surveyed,with related mechanisms,technical details and performance analysis.

关键词： Rockburst prediction burst liability Artificial neural network Support vector machine Deep learning

Assessment of digital image correlation method in determining large scale cemented rockfill strains

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International Journal of Mining Science and Technology 2019年第5期29卷 771-776页

作者： bob A.Lingga derek b.apel Mohammadali Sepehri Yuanyuan Pu School of Mining and Petroleum Engineering University of AlbertaEdmonton T6G 2W2Canada

A conventional contact method(using linear transducers)and a non-contact method are deployed to measure the axial and lateral deformations of large scale cylindrical cemented rockfill *** works incorporating two pinhole cameras to create one stereovision by digital image correlation shows that the non-contact method is as reliable for testing large cylindrical specimens as measurements done by using linear variable displacement transformer and string *** this particular large specimen,the experiment resulted in the acceptable mean difference between lateral strain using both methods is 5.1 percent,and 14.5 percent for the axial *** occurrence is inevitable due to the heterogeneity of the concrete system and the placement of the monitoring point in digital image correlation method,although the comparison of stress-strain relationship in both methods still indicates a *** on the results of the present experiments,the authors recommend the noncontact method for a detailed investigation of the material behavior during the uniaxial compressive strength *** field strain measurement enables this digital method to examine local strains near cracks at any point,a very useful tool for studying material deformation behavior.

关键词： Experimental testing Cemented rockfill Digital image correlation Strain measurement Mine backfill

Evaluation of the performance of yielding rockbolts during rockbursts using numerical modeling method

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International Journal of Coal Science & Technology 2022年第6期9卷 25-50页

作者： Jun Wang derek b.apel Huawei Xu Chong Wei School of Mining and Petroleum Engineering University of AlbertaT6G 2R3 EdmontonABCanada

Rockburst;Rockburst damage;Yielding rockbolt;Numerical modeling;UDEC;Underground miningThe assessment of yielding rockbolt performance during rockbursts with actual seismic loading is essential for rock-burst supporting *** this paper,two types of yielding rockbolts(D-bolt and Roofex)and the fully resin-grouted rebar bolt are modeled via the"rockbolt"element in universal distinct element code(UDEC)after an exact calibration procedure.A two-dimensional(2D)model of a deep tunnel is built to fully evaluate the performance(e.g.,capacity of energy-absorption and control of rock damage)of yielding and traditional rockbolts based on the simulated *** influence of different rockburst magnitudes is also *** results suggest that the D-bolt can effectively control and mitigate rockburst damage during a weak rockburst because of its high strength and deformation *** Roofex is too"soft"or"smooth"to limit the movement of ejected rocks and restrain the large deformation,although it has an excellent deformation *** resin-grouted rebar bolt can maintain a high axial force level during rockbursts but is easy to break during dynamic shocks,which fails to control rapid rock bulking or *** types of rockbolts cannot control the large deformation and mitigate rockburst damage effectively during violent *** rockburst damage severity can be significantly reduced by additional support with cable *** study highlights the effectiveness of numerical modeling methods in assessing the complex performance of yielding rockbolts during rockbursts,which can provide some references to improve and optimize the design of rock supporting in burst-prone grounds.

关键词： Rockburst Rockburst damage Yielding rockbolt Numerical modeling UDEC Underground mining

Use of machine learning algorithms to assess the state of rockburst hazard in underground coal mine openings

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Journal of Rock Mechanics and Geotechnical Engineering 2022年第3期14卷 703-713页

作者： Lukasz Wojtecki Sebastian Iwaszenko derek b.apel Mirosawa bukowska Janusz Makówka Central Mining Institute Katowice40-166Poland School of Mining and Petroleum Engineering University of AlbertaEdmontonT6G 2R3Canada

The risk of rockbursts is one of the main threats in hard coal mines. Compared to other underground mines, the number of factors contributing to the rockburst at underground coal mines is much *** such as the coal seam tendency to rockbursts, the thickness of the coal seam, and the stress level in the seam have to be considered, but also the entire coal seam-surrounding rock system has to be evaluated when trying to predict the rockbursts. However, in hard coal mines, there are stroke or stress-stroke rockbursts in which the fracture of a thick layer of sandstone plays an essential role in predicting rockbursts. The occurrence of rockbursts in coal mines is complex, and their prediction is even more difficult than in other mines. In recent years, the interest in machine learning algorithms for solving complex nonlinear problems has increased, which also applies to geosciences. This study attempts to use machine learning algorithms, i.e. neural network, decision tree, random forest, gradient boosting, and extreme gradient boosting(XGb), to assess the rockburst hazard of an active hard coal mine in the Upper Silesian Coal basin. The rock mass bursting tendency index WTGthat describes the tendency of the seam-surrounding rock system to rockbursts and the anomaly of the vertical stress component were applied for this purpose. Especially, the decision tree and neural network models were proved to be effective in correctly distinguishing rockbursts from tremors, after which the excavation was not damaged. On average, these models correctly classified about 80% of the rockbursts in the testing datasets.

关键词： Hard coal mining Rockburst hazard Machine learning algorithms

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

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Journal of Rock Mechanics and Geotechnical Engineering 2021年第2期13卷 457-478页

作者： Jun Wang derek b.apel Yuanyuan Pu Robert Hall Chong Wei Mohammadali Sepehri School of Mining and Petroleum Engineering University of AlbertaEdmontonAlbertaT6G 2R3Canada State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing UniversityChongqing400044China

As the depth of excavation increases,rockburst becomes one of the most serious geological hazards damaging equipment and facilities and even causing fatalities in mining and civil *** has forced researchers worldwide to identify different methods to investigate rockburst-related ***,some problems,such as the mechanisms and the prediction of rockbursts,continue to be studied because rockburst is a very complicated phenomenon influenced by the uncertainty and complexity in geological conditions,in situ stresses,induced stresses,*** modeling is a widely used method for investigating *** date,great achievements have been made owing to the rapid development of information technology(IT)and computer ***,it is necessary and meaningful to conduct a review of the current state of the studies for rockburst numerical *** this paper,the categories and the origin of different numerical approaches employed in modeling rockbursts are reviewed and the current usage of various numerical modeling approaches is investigated by a literature ***,a state-of-the-art review is implemented to investigate the application of numerical modeling in the mechanism study,and prediction and prevention of *** main achievements and problems are ***,this paper discusses the limitations and the future research of numerical modeling for *** approach is proposed to provide researchers with a systematic and reasonable numerical modeling framework.

关键词： Rockburst Numerical modeling Rockburst mechanism Dynamic modeling

Analysis of the damage mechanism of strainbursts by a global-local modeling approach

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Journal of Rock Mechanics and Geotechnical Engineering 2022年第6期14卷 1671-1696页

作者： Jun Wang derek b.apel Artur Dyczko Andrzej Walentek Stanislaw Prusek Huawei Xu Chong Wei School of Mining and Petroleum Engineering University of AlbertaEdmontonAlbertaT6G 2R3Canada Jastrze˛bska Spółka We˛glowa S.A.Group Aleja Jana Pawła II 4Jastrze˛bie-Zdrój44-330Poland Central Mining Institute Plac GwarkówKatowice140-166Poland

Strainburst is the most common type of *** research of strainburst damage mechanisms is helpful to improve and optimize the rock support design in the burst-prone *** this study,an improved global-local modeling approach was first adopted to study strainburst damage *** extracted stresses induced by multiple excavations from a three-dimensional(3D)global model established by fast Lagrangian analysis of continua in 3 dimensions(FLAC3D)are used as boundary conditions for a two-dimensional(2D)local model of a deep roadway built by universal distinct element code(UDEC)to simulate realistic stress loading paths and conduct a detailed analysis of rockburst damage from both micro and macro *** results suggest that the deformation and damage level of the roadway gradually increase with the growth of surrounding rock stress caused by the superposition of mining-or excavation-induced stresses of the panel and nearby *** significant increase of surrounding rock stresses will result in more accumulated strain energy in two sidewalls,providing a necessary condition for the strainburst occurrence in the dynamic *** strainburst damage mechanism for the study site combines three types of damage:rock ejection,rock bulking,and *** the strainburst,initiation,propagation,and development of tensile cracks play a crucial role in controlling macroscopic failure of surrounding rock masses,although the shear crack always accounts for the main proportion of damage *** deformation and damage level of the roadway during a strainburst positively correlate with the increasing peak particle velocities(PPVs).The yielding steel arch might not dissipate kinetic energy and mitigate strainburst damage effectively due to the limited energy absorption *** principles to control and mitigate strainburst damage are proposed in this *** study presents a systematic framework to investigate strainburst damage mechanisms

关键词： Strainburst Numerical modeling Damage mechanism Finite difference method(FDM) Discrete element method(DEM) Underground mining

不同应力路径下含瓦斯煤的声发射特性与能量演化规律

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中南大学学报（自然科学版） 2023年第6期54卷 2323-2337页

作者：陈结张允瑞蒲源源杜俊生舒龙勇赵旭生张志刚 derek b.apel 重庆大学资源与安全学院重庆400044 重庆大学煤矿灾害动力学与控制国家重点实验室重庆400044 煤炭科学技术研究院有限公司安全分院北京100013 煤炭科学研究总院煤炭资源高效开采与洁净利用国家重点实验室北京100013 中煤科工集团重庆研究院有限公司重庆400037 阿尔伯塔大学石油与矿业工程学院加拿大埃德蒙顿T6G 2R3

为了研究含瓦斯煤在不同扰动作用下的声发射特性和能量演化规律,利用多场煤与瓦斯突出过程宏细观试验系统,开展6种应力路径下的含瓦斯煤轴向加卸载试验,分析应力路径对含瓦斯煤声发射特性和变形特性的影响,并得到含瓦斯煤在循环加卸载... 详细信息

为了研究含瓦斯煤在不同扰动作用下的声发射特性和能量演化规律,利用多场煤与瓦斯突出过程宏细观试验系统,开展6种应力路径下的含瓦斯煤轴向加卸载试验,分析应力路径对含瓦斯煤声发射特性和变形特性的影响,并得到含瓦斯煤在循环加卸载过程中的能量演化特征及储能规律。研究结果表明:含瓦斯煤在吸附过程中的振铃计数随吸附时间增长而减少,根据出气口压力变化趋势将吸附过程分为3个阶段,分别为外扩散阶段、内扩散阶段和吸附饱和阶段;含瓦斯煤在加卸载过程中的振铃计数主要分布在应力上升区段,出现了明显的Kaiser效应,累计振铃计数在循环加卸载路径下呈“阶梯”形增长,且随着循环次数增加和应力路径延长而增大;含瓦斯煤在不同循环加卸载路径下的能量演化规律具有一致性,各能量密度均随着轴向应力增加而呈现二次函数型增长,并经历了减速增长、线性增长和加速增长的3个阶段;同时,弹性能密度和总输入能密度之间存在线性关系,储能系数为定值且均在50%以上。

关键词：应力路径加卸载含瓦斯煤声发射能量演化

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