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Record W3176615821 · doi:10.82308/37055

Geotechnical risk assessment of mine haulage drifts during the life of a mine plan

2013· article· en· W3176615821 on OpenAlexfundaboutno aff
Wael Rashad Elrawy Abdellah

Bibliographic record

VenueeScholarship@McGill (McGill) · 2013
Typearticle
Languageen
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHaulageMining engineeringGeologyPlan (archaeology)Geotechnical engineeringGeotechnical investigationUnderground mining (soft rock)Coal miningEngineeringWaste management

Abstract

fetched live from OpenAlex

Mine developments such as haulage drifts and cross-cuts are the primary access to the mining blocks of an orebody in multilevel mining systems for tabular ore deposits. Thus, their stability is of utmost importance during the planned period of production or the life of a mine plan. Many Canadian underground mines use longitudinal and transverse stoping with delayed backfill to extract tabular ore deposits. These methods require access to the orebody through a number of sill drives or cross-cuts which link the orezone to the haulage drift hence creating intersections on multiple levels. Mine development instability could lead to serious consequences such as injuries, production delays and higher operational cost. The objective of this research is to develop a hybrid approach in which deterministic numerical modelling is integrated with probabilistic methods to evaluate the stability of mine developments due to nearby mining activity. A case study comprising four consecutive mine levels in a deep underground metal mine in Sudbury, Ontario has been adopted for this study. The stability performance of the haulage drift is assessed using two separate evaluation criteria, namely Mohr-Coulomb yield function and Brittle Shear Failure. Random Monte-Carlo (RMC) technique is then employed in conjunction with Finite difference modelling software FLAC to determine the probability of instability or unsatisfactory performance of the haulage drift with respect to nearby mining sequence. In this study, the haulage drift performance is considered unsatisfactory when the yield zones or brittle shear failure around the haulage drift extend beyond the anchorage limit of the rock support. A comparison of the results from Mohr-Coulomb and Brittle Shear conditions has revealed that Mohr-Coulomb is more conservative from a design point of view. A three-dimensional, elastoplastic, finite difference model (FLAC 3D) is then constructed to simulate the case study mining orezone. The unsatisfactory performance of the intersection is evaluated with respect to mining sequence in terms of the strength-to-stress ratio computed by FLAC3D. Unsatisfactory stability performance is defined by a strength-to-stress ratio that is less than 1.4 and its corresponding extent into the rockmass around the intersection. Due to the large size of the FLAC3D model, the probabilistic simulations are conducted with the Point-Estimate Method (PEM), which requires significantly lesser number of simulations than Random Monte-Carlo (RMC). The results are presented and categorized with respect to probability, instability, and mining stage. In order to validate the numerical model, Multi-point borehole extensometers (MPBX) are installed at selected intersections to monitor the rock deformations as mining activities progress. The monitoring results revealed a lateral shift of the drift walls toward the orebody and much less deformations in the drift back. Finally, a methodology is developed to estimate the geotechnical risk of drift instability by considering the probability of failure and cost of consequence of such failure at an intersection. A 5-level risk index is derived which ranges from low to extreme. The methodology is demonstrated through an intersection from the case study mine, and the risk index is shown to vary with mining sequence. It is shown that the risk-index methodology can be used to confirm the need for enhanced supports, but it can also be used as basis for the comparison alternative mine designs.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.211
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 teacher head, not a consensus.

Study designBench or experimental
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

Citations9
Published2013
Admission routes2
Has abstractyes

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