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Record W4396771668 · doi:10.1061/ijgnai.gmeng-9430

Asymmetric Dynamic Support for Roadways in Subvertical Coal Seams

2024· article· en· W4396771668 on OpenAlexaff
Shengquan He, Feng Shen, Tuo Chen, Dazhao Song, Xueqiu He, Jianqiang Chen, Ting Ren, Zhenlei Li

Bibliographic record

VenueInternational Journal of Geomechanics · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsMcGill University
Fundersnot available
KeywordsGeologyCoal miningMining engineeringCoalGeotechnical engineeringSeismologyEngineering

Abstract

fetched live from OpenAlex

Due to the unique conditions of the Wudong subvertical coal seam, damage to the underground roadway occurs frequently during the coal mining process. With the increase in mining depth, the energy and incidence of microseismic events increase significantly, showing characteristics of zoning and grading along the strike. Therefore, the damage to the underground roadway of the Wudong coal seam was studied with a focus on dynamic load disturbance. The results showed that the underground roadway damage exhibits asymmetric characteristics, with significant sinking on the north shoulder and various degrees of bulging on both sides of the roadway. The existing support scheme in the mine could not effectively control the deformation and damage to the rock surrounding the underground roadway under the action of dynamic loads. Therefore, the asymmetric support scheme with the high prestressed anchoring long and short anchor cable network was proposed to provide targeted reinforcement for the underground roadway, which has been shown to effectively mitigate the deformation of the surrounding rock. Eventually, considering the characteristics of microseismic event distribution and the observed increase in the rock damage with the increase of the seismic source energy, a segmented and asymmetric support scheme was suggested to tactically support the underground roadway. The findings of this study could potentially improve the ground safety of underground roadways under similar mining conditions.

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: none
Teacher disagreement score0.975
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.006
GPT teacher head0.244
Teacher spread0.238 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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