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Record W2974149634 · doi:10.3390/app9183891

Dome Roof Fall Geohazards of Full-Seam Chamber with Ultra-Large Section in Coal Mine

2019· article· en· W2974149634 on OpenAlexaff
Rui Gao, Hongchun Xia, Kun Fang, Chunwang Zhang

Bibliographic record

VenueApplied Sciences · 2019
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversity of Ottawa
FundersState Key Laboratory of Coal Resources and Safe MiningChina Postdoctoral Science FoundationChina University of Mining and TechnologyNational Natural Science Foundation of China
KeywordsRoofDome (geology)GeologyCoal miningGeotechnical engineeringCoalMining engineeringStructural engineeringEngineeringGeomorphology

Abstract

fetched live from OpenAlex

The roof fall hazard is more likely to take place within chamber with ultra-large section, which would not only damage mechanical equipment, but also cause casualties. In this paper, the strap joint chamber of the Tashan coal mine is studied, and finite and discrete element method (FDEM) is used to establish the numerical model of the roof fall of the chamber dome. The simulation results show that the chamber dome mainly undergoes shear failure and forms a large number of cracks. With further development and penetration of cracks, a distinct roof separation is found in the chamber dome. When the crack develops to the dome surface of the chamber, under the effect of the mine pressure, the coal body is separated from the surface of the chamber and the roof fall hazard occurs. Based on the mechanism of roof fall hazard of the chamber dome, it is concluded that improving the shear strength of the surrounding rock and reducing the crack penetration are the main ways to control the roof fall. Therefore, the high-strength anchor bolt and cable support is adopted to fill the cracks and improve the shear strength of the surrounding rock. The result showed that the roof separation of the chamber dome in the field is confined to 0.012 m. The surrounding rock is well controlled and no roof fall occurs.

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)0.000
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 score0.298
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

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