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Record W3194920972 · doi:10.82308/43699

Nonlinear rock mass behaviour and application to stability of underground haulage drift

2006· article· en· W3194920972 on OpenAlexaboutno aff
Yaohua Zhang

Bibliographic record

VenueeScholarship@McGill (McGill) · 2006
Typearticle
Languageen
FieldEngineering
TopicGeoscience and Mining Technology
Canadian institutionsnot available
Fundersnot available
KeywordsHaulageRock mass classificationStability (learning theory)Nonlinear systemMining engineeringGeologyUnderground mining (soft rock)Geotechnical engineeringEnvironmental scienceEngineeringComputer scienceStructural engineeringWaste managementPhysicsCoal mining

Abstract

fetched live from OpenAlex

Numerical methods of analysis such as the finite element method and finite difference method have seen increasing use in recent years as tools for geomechanical mine design to predict problems of ground caving and failure. As a result of recent advances in computer technology, it is now possible to handle large-scale problems involving complex material and geometric nonlinearities at an affordable computational cost. The scope of this study is the stability of underground mine haulage drifts associated with sublevel stoping method with delayed backfill. This is one of the most popular mining methods today in Canadian underground metal mines. In this method, blasted ore is mucked with load-haul-dump vehicles and transported to the nearest dump through a nearby haulage drift. Therefore, it is crucial in a mining operation that a haulage drift remains functional during the life of the stope. This study is focused on studying the interaction between the haulage drift and nearby mining activity. The stability of the haulage drift is examined through a detailed parametric study of a finite element model representing typical mining layout most commonly adopted in Canadian underground metal mines. The model parametric study examines the influence of critical factors such as the stope mining sequences, mining depth and the distance between the stope and the haulage drift. The model is set up for nonlinear behaviour of the rock mass taking into account elastoplasticity of the rock mass and non-associated plasticity using Mohr Coulomb and Drucker Prager yield functions. Stability indicators are defined in terms of displacement, stress and the extent of yield zones. These indicators serve as a basis for assessing the effect of different parameters on the stability of the haulage drift. From the model parametric study, it is found that stope mining causes a lateral movement of the entire drift. The severity of such movement is increased with shorter distance between the stope and haulage drift. Of all mining sequences examined, same-level mining is the most critical step. It is also found that more yield zones develop around the haulage drift as the mining depth increases and as distance between haulage drift and the stope decreases. A 3-centre arc drift is compared with a rectangular one of the same cross sectional area. It is found that the 3-centre arc drift shape is more stable. This study also demonstrates that the nonlinear elastoplastic analysis gives more realistic results than traditional linear elastic analysis in terms of stress and displacement behaviour of the haulage drift.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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 designObservational
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

Citations4
Published2006
Admission routes1
Has abstractyes

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