New ventilation design criteria for underground metal mines based upon the "life-cycle" airflow demand schedule
Bibliographic record
Abstract
Presently, mine ventilation systems are designed more towards the “worst-case-scenario” with respect to airflow demand, which usually occurs well in the future of a mine’s operating life. Consequently, within the early stages of operation, the mines’ intake air volume could be well in excess of their “true” ventilation needs. Such ventilation systems are inefficient and this design approach needs to change if Canadian mines are to remain competitive while attempting to reduce their carbon footprints. This thesis introduces a new method that can be used to evaluate the efficiency of large and complex underground ventilation systems. This new evaluation method is based upon the magnitude of a mine’s potential “ventilation redundancy” that can be used to gauge the efficiency of its ventilation system. Two conventionally analyzed case studies presented in this thesis highlight the complexity and difficulty in determining the ventilation redundancy in large and deep metal mines. Challenges include gaining adequate data to assess the dynamic nature of the production activities that continually redefine where ventilation is required. To address this issue, this thesis introduces a novel method, where a multi-level mining block’s activity based intake air volume is determined through discrete-event mining process simulation using AutoModTM. In accordance with the number of active mining blocks that will be required to achieve future production requirements, the mine’s “traditional” and “activity based” life-cycle airflow demand schedule is subsequently determined. Furthermore, based upon the life-cycle airflow demand schedule the mine’s primary and auxiliary ventilation systems are solved through ventilation simulation. The output data generated through ventilation simulation was then used to determine the economic and environmental benefits of an “activity based” ventilation system versus a “traditional” ventilation system. This new ventilation design concept, which is based upon the mine’s life-cycle airflow demand schedule determined through discrete-event process simulation can fundamentally change the way underground ventilation systems are presently designed and operated. This can be extremely important for the reason that besides providing adequate airflow to the production workings, this new design approach would assist the mines to reduce their energy consumption and consequently their GHG emissions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".