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

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

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Seismic evaluation of the destress blasting efficiency

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Journal of Rock Mechanics and Geotechnical Engineering 2022年第5期14卷 1501-1513页

作者： Krzysztof Fuławka Piotr Mertuszka Witold Pytel Marcin Szumny Tristan Jones Research and Development Centre KGHM Cuprum Ltd.Wrocław53-659Poland Luossavaara-Kiirunavaara AB(LKAB) MalmbergetSE-98381Sweden

In this paper, selected methods of destress blasting efficiency assessment are presented, and novel quantitative methods based on in situ seismic measurements are proposed. The newly formulated solution combines two different approaches. The first, which is useful mostly for the near-field seismic analyses, is based on the analysis of seismic amplitude characteristics, and the second, relevant for farfield evaluation, is extended by the duration and frequency of the seismic wave. Both approaches are based on the seismic analyses of the waveforms generated by blasting recorded by the local seismic network. The proposed solutions are tested and validated in deep underground mines in Poland in which the room-and-pillar mining method is applied. Based on performed analysis, it is shown that both methods may be used as a rockburst hazard control in underground mines. However, developed methods may also be successfully implemented in other engineering practices, including the assessment of seismic vibrations in open pits and quarries.

关键词： rockburst hazard Destress blasting Induced seismicity Seismic events Dominant frequency

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Numerical modeling of destress blasting for strata separation

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第9期15卷 2238-2249页

作者： Petr Konicek Tuo Chen Hani S.Mitri Institute of Geonics Czech Academy of SciencesOstrava70800Czech Republic Department of Mining and Materials Engineering McGill UniversityMontrealH3A 0E8Canada

Destress blasting(DB)implemented along the perimeter of safety pillars is a special application of destressing in coal longwall *** goal is to separate relatively more deformed mined areas from safety pillars,such as shaft pillars or cross-cut pillars,to reduce the transfer of high stresses to the protective *** case study aims to numerically simulate selected destress blasts in the Czech part of the Upper Silesian Coal Basin and examine its impact on stress transfer to the safety pillar *** separate the area between the protective pillar and the longwall(LW),two fans of five 93-mm blast holes(length of 93e100 m)were drilled from the gate roads into the overburden *** set of blast holes was fired separately in two stages without time *** explosive charge(gelatin-type of explosive)of each stage is 3450 *** two DB stages were fired when the longwall face was approximately 158 m and 152 m away from the blast.A 3D mine-wide model is built and validated with in situ stress measured with *** and destressing in three 5-m thick coal seams are simulated in the *** modeling of DB is successfully conducted using a rock fragmentation factor a of 0.05 and a stress reduction/dissipation factor β of *** of transfer of additional stress from the mining area into the safety pillar is evaluated by comparison of yielding volume before and after *** is shown that yielding volume drops after DB by nearly 80%in the area of the destressing panel and near the safety shaft pillar.

关键词： rockburst hazard Destress blasting(DB) Strata separation Safety pillar Numerical modeling Fragmentation factor Stress dissipation factor Longwall mining

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rockburst risk control and mitigation in deep mining

Deep Resources Engineering

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Deep Resources Engineering 2024年第2期1卷 46-67页

作者： Ming Cai School of Engineering and Computer Science Laurentian UniversitySudburyONCanada MIRARCO-Mining Innovation Laurentian UniversitySudburyONCanada Key Laboratory of Ministry of Education for Safe Mining of Deep Metal Mines Northeastern UniversityShenyangChina

It is important to understand and manage rockburst challenges in deep mining *** paper presents a systematic study of rockburst risk in underground mining,offering a detailed examination of influencing factors,risk assessment,and various control and mitigation *** complexities of rockburst phenomena are explained by examining factors that lead to the occurrence of rockbursts.A rockburst risk assessment using a bow-tie analysis is conducted,which provides insights into both risk evaluation and proactive control and mitigation *** core of the paper presents a comprehensive array of rockburst risk control and mitigation methods,which range from controls to reduce rockburst hazard,and excavation vulnerability,to controls and mitigations to reduce *** engineering control methods,including mine design and mining sequencing,are *** engineering control measures,such as ground pre-conditioning and rock support,are scrutinized,along with administrative controls like evacuation and re-entry protocols and the use of mechanized equipment.A multiple-line defense system is advocated for rockburst risk management to address the uncertainties involved in the ***,emerging technologies and innovations as well as challenges are discussed,providing a roadmap for continued advancements in rockburst risk management in the *** work serves as a valuable resource for mining professionals,researchers,and policymakers seeking a comprehensive understanding of rockburst risk management in deep mining.

关键词： rockburst risk rockburst hazard Excavation vulnerability Exposure Rock support Risk control Risk mitigation

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