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Record W2785193314 · doi:10.1139/cgj-2016-0631

Comparison of rockburst occurrence during extraction of thick coal seams using top-coal caving versus slicing mining methods

2018· article· en· W2785193314 on OpenAlexvenueno aff
Zhenlei Li, Xueqiu He, Linming Dou, Dazhao Song

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesKey ProgrammeState Key Laboratory of Coal Resources and Safe MiningChina University of Mining and TechnologyNational Natural Science Foundation of China
KeywordsCoal miningMining engineeringGeologySlicingCoalGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

In recent years, rockbursts have occurred frequently during the mining of thick coal seams in China. Use of the top-coal caving or slicing mining method to extract these thick seams may result in distinct geomechanical responses in the strata and, in turn, the pattern of rockburst occurrence around longwall layouts. To establish a thorough understanding of which method (caving or slicing) is better when it comes to preventing rockbursts during the extraction process, a suite of in situ rockburst measurements was conducted. Six typical rockburst-prone collieries were monitored during which a total of 110 rockburst events occurred. Numerical modelling was used to help interpret the observations. Here, we focus on the analysis of these field observations and the numerical simulations employed to develop a conceptual model for rockburst occurrence during caving mining of thick coal seams. We find that caving mining has a certain rockburst-reducing effect in that the method significantly decreases, or even avoids, the occurrence of rockbursts at coalfaces. Moreover, it reduces the scope of the damage likely to be incurred and the severity and frequency of rockbursting. According to the conceptual model, the rockburst-prone area during caving mining is generally the roadway section located a certain distance ahead of the coalface. This distance, which is roughly 10–54 m, is consistent with the rockburst damage observed on site (mostly 10–50 m ahead of the coalface). This rockburst pattern arises because caving mining results in reduced stress concentration, less bottom coal being retained, and wider-ranging fracture zones around the mine openings, especially ahead of the coalface. This makes the rock surrounding the mine openings less likely to accumulate high levels of elastic energy that need releasing and hence it is more difficult to induce rockbursting. Therefore, it is recommended that the top-coal caving method should be the preferred method of extraction when mining coal seams of a certain thickness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.361
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations40
Published2018
Admission routes1
Has abstractyes

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