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Record W4386495600 · doi:10.56952/arma-2023-0739

Numerical Investigation on the Impact of Drift Geometry Representation on the Assessment of Wedge Formation Using DFN Modelling in Underground Hard Rock Mines

2023· article· en· W4386495600 on OpenAlexaff
C. W. Durham, Martin Grenon, Efstratios Karampinos, J.F. Dorion

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsGlencore (Canada)Université Laval
Fundersnot available
KeywordsClassification of discontinuitiesExcavationRock mass classificationWedge (geometry)GeologyGeotechnical engineeringMining engineeringStability (learning theory)GeometryComputer scienceMathematics

Abstract

fetched live from OpenAlex

ABSTRACT Geological discontinuities have a large impact on the rock mass behavior in underground excavations. Under low stress conditions, structurally controlled wedge failure is one of the most critical types of rock instability. The stability analysis, in this case, is essential to consider both the rock mass fracture network and the geometry of the opening. However, current wedge stability analysis tools do not typically examine the detailed geometrical characteristics of the rock discontinuities and the excavation shape in 3D. This paper reports on the development of a comprehensive and more rational numerical approach to assess wedge formation around underground mine openings. The approach considers the structural rock mass complexity using Discrete Fracture Network (DFN) modelling and the detailed 3D underground excavation profile obtained from surveying. The developed methodology was successfully applied to estimate the formation of wedges around an excavation in an underground mine. A detailed investigation on the 3D profile and shape of the excavation indicated that an oversimplification of the excavation geometry in the stability analysis can result in inadequate assessment of wedge formation. Further analysis allowed to identify elongated wedges that may not be critical from a stability perspective and wedges that were not entirely formed in the DFN model but may still be critical for the stability of the excavation. INTRODUCTION Under low-stress conditions, the stability of mining excavations is frequently controlled by rock discontinuities (Hoek et al., 2000). Wedges are formed by the intersection of more than two discontinuities on the walls of an underground opening. The structurally defined rock blocks can fall or slide toward the excavation. The most common wedges in the field are tetrahedral blocks defined by the intersection of three fractures and the surface of the underground opening (Windsor, 1999). Under these conditions, analyzing the size distribution and probability of occurrence of wedges is critical for the design and support of underground excavations.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.130
GPT teacher head0.325
Teacher spread0.195 · 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 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
Published2023
Admission routes1
Has abstractyes

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