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Shear rupture – two case studies from a deep mine

2014· article· en· W2623046060 on OpenAlexaff
Rob Bewick, Peter K. Kaiser, W.F. Bawden

Bibliographic record

VenueDeep mining · 2014
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsLaurentian UniversityWomen's and Gender Studies et Recherches FéministesGolder Associates (Canada)
Fundersnot available
KeywordsGeologyMicroseismShear (geology)BrittlenessSlip (aerodynamics)Fault (geology)SeismologyRock mass classificationShear stressStress fieldGeotechnical engineeringMechanicsStructural engineeringPetrologyEngineeringMaterials scienceFinite element methodComposite material

Abstract

fetched live from OpenAlex

When a fault-slip event mechanism is determined, it is easy to assume that there must be a fault present to generate the event. A pre-existing fault is not needed to create a fault-slip event. Fault rupture (the failure process in brittle rocks which occurs under confined conditions) also generates a fault-slip focal mechanism. Fault ruptures will commonly occur far from mining, in abutments, wide pillars, and sills. First the rupture process is overviewed. Then two mining fault rupture case examples are summarised to show the fault rupture process, final rupture geometry, and energy release potential observed in the field conform to theoretical understanding. In this article it is shown that the fault rupture process and energy release depends on the boundary condition (system stiffness) surrounding the failure process. While seemingly theoretical, the findings have practical significance with respect to rock mass characterisation, microseismic monitoring, rock mass behaviour back analysis, and mining strategy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0040.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.251
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations3
Published2014
Admission routes1
Has abstractyes

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