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Record W2305081595 · doi:10.14288/1.0081178

Operating risk : planning for flexible mining systems

2009· article· en· W2305081595 on OpenAlexaffabout
Vassilios Kazakidis

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRisk analysis (engineering)BusinessComputer science

Abstract

fetched live from OpenAlex

This research contributes to understanding the interaction between ground-related problems and mining systems as a basis for the development of flexible mining systems. It has demonstrated that ground-related problems impose a significant operating risk factor that requires particular attention in proactive mine planning and design. A new philosophy for quantifying the impact of ground-related problems and assessing the links between mine planning and geomechanics was established. The various types of potential problems were classified based on review of case studies and the surveillance of ground failures in several underground hard rock mines of the Sudbury Basin. It was demonstrated that, despite serious efforts in the design of underground mines, ground-related problems still cannot be totally avoided. A time-dependent internal risk model was established to quantify the impact of ground-related problems in mine production systems. Subjective probabilities provide the input for a reliability analysis, which derives the required input parameters for production simulation. Reliability analyses that are currently used to calculate the reliability of mine equipment were applied for the case of mine subsystems with ground-related problems. A cost impact model that is dependent on the parameters determined in a reliability analysis was introduced. Flexibility needs in mine planning and design, with respect to ground-related problems, were analyzed through conventional discounted cash flow analysis, real options analysis, production simulation, and Monte-Carlo simulation. Approaches that are currently applied in investment science and decision making were evaluated in terms of their applicability to evaluate such flexibility needs in mining systems. A methodology that includes the applicability of project valuation analyses to assess flexible mining systems with respect to potential ground-related problems, along with a flexibility index, were introduced. Their applicability is demonstrated through test case studies. Contingency planning and flexibility assessment by such means can be integrated into future mine production systems to account for the potential risk of ground-related problems for more proactive mine planning and design.

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)0.003
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.180
Teacher spread0.167 · 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

Citations9
Published2009
Admission routes2
Has abstractyes

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