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Record W2765929829 · doi:10.1016/j.jrmge.2017.07.002

Voussoir beam model for lower strong roof strata movement in longwall mining – Case study

2017· article· en· W2765929829 on OpenAlexaff
Chuang Liu, Huamin Li, Hani S. Mitri, Dongjie Jiang, Junfa Feng

Bibliographic record

VenueJournal of Rock Mechanics and Geotechnical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsMcGill University
FundersNational Natural Science Foundation of China
KeywordsRoofShieldLongwall miningGeologyCoal miningMining engineeringBeam (structure)Geotechnical engineeringDrillCoalPetrologyStructural engineeringEngineering

Abstract

fetched live from OpenAlex

The paper presents the influence of varying immediate roof thickness on the lower strong roof strata movement and failure pattern in longwall coal mining with large mining height. The investigation is based on 58 geological drill holes and hydraulic shield pressure measurements around the longwall Panel 42105 of the Buertai Mine in Inner Mongolia Autonomous Region, China. The longwall Panel 42105 is characterized by relatively soft immediate roof strata of varying thickness superposed by strong strata, herein defined as lower strong roof. A voussoir beam model is adopted to interpret the structural movement of the lower strong roof strata and shield pressure measurements. It is shown that when the immediate roof is relatively thick, the broken overlying lower strong roof tends to form a stable voussoir beam with previously broken layer, thus not exerting high pressure on the hydraulic shield and working face. When the immediate roof is relatively thin, the broken overlying lower strong roof tends to behave as a cantilever beam, thus exerting higher pressure on the hydraulic shield and working face. Comparison of model predictions with measured time-weighted average shield pressure (TWAP) shows good agreement.

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 categoriesMeta-epidemiology (narrow)
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 score0.562
Threshold uncertainty score1.000

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 integrity0.0000.000
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 head0.023
GPT teacher head0.252
Teacher spread0.229 · 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.

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

Citations41
Published2017
Admission routes1
Has abstractyes

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