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Orthogonal array analysis of overburden failure due to mining of multiple coal seams

2019· article· en· W2990092193 on OpenAlex

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affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Southern African Institute of Mining and Metallurgy · 2019
Typearticle
Languageen
FieldEngineering
TopicGeomechanics and Mining Engineering
Canadian institutionsGeomechanica (Canada)
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsChina Scholarship CouncilUniversity of the Pacific
KeywordsOverburdenCoal miningMining engineeringGeologyCoalGeotechnical engineeringPetroleum engineeringEngineeringWaste management

Abstract

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This paper presents a numerical analysis that uses an orthogonal array to investigate overburden failure caused by longwall mining of multiple coal seams. An LN(s k ) array is said to be an orthogonal array with s levels, N rows, and k columns. This analysis identifies the contrasting factors that influence the height of the caving and water-conducting fractured zones. The factors include the mechanical properties of the interburden layers (factor A), thickness of the interburden layers (factor B), and mining height of the lower seam (factor C). The mechanical properties of the overburden failure are quantitatively investigated and the correlations among the factors are evaluated. The results show that factors A, B, and C all have a significant influence on the interactions during mining of multiple seams. This means that mining of the lower seam significantly changes the height of the caving zone of the entire system, with factors B and C having the most influence. Factor B has a more obvious effect on the waterconducting fractured zone than factor A, but factor C has the greatest effect among the factors. An equation to describe a dividing line, which is set to denote the relationship between the non-interaction ratio (K) and the cutting height of the lower seam (M) is proposed. This modified dividing line can be used to determine whether interactions exist among the overburden failure zones.

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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 score0.305
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.182
Teacher spread0.176 · 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