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Record W2945405524 · doi:10.2298/tsci180907215g

Variation law of coal permeability under cyclic loading and unloading

2019· article· en· W2945405524 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

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

Bibliographic record

VenueThermal Science · 2019
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsGeomechanica (Canada)
FundersFundamental Research Funds for the Central UniversitiesChina University of Mining and Technology
KeywordsCoalPermeability (electromagnetism)Materials scienceOverburden pressureGeotechnical engineeringPlasticityComposite materialCoal miningStress pathShear (geology)Scanning electron microscopeGeologyEngineeringChemistry

Abstract

fetched live from OpenAlex

In the excavation process, the coal pillar will undergo shear failure due to repeated loading and unloading from mining stress. Meanwhile, plastic flow will occur after shear failure. The permeability change of the coal pillar under plastic flow is closely related to the loading path. Through a permeability test of the coal sample after shear yielding under cyclic loading and unloading conditions, the variation law of permeability of a coal seam under plastic flow was obtained. The results show that the permeability of the coal sample increases as the axial strain decreases during the unloading phase. During the loading phase, as the axial strain increases, the permeability of the coal sample decreases. Scanning electron microscope tests show that the crack opening is larger at lower confining pressures. As the confining pressure increases, the crack opening decreases and moves toward the middle of the sample.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.181

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 head0.012
GPT teacher head0.219
Teacher spread0.207 · 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