Optimization of the Combined Ventilation System for Dust Reduction in Blind Headings of Potash Mines
Bibliographic record
Abstract
Ensuring safe and comfortable working conditions for miners in potash mines is an urgent and unresolved problem, primarily due to the high intensity of dust emissions.This is especially true for poorly studied situations when the main dust source is the area of ore transfer from the borer miner to the shuttle car.In this paper, we explore the possibilities of reducing dustiness in the atmosphere of a blind heading with an operating borer miner through the implementation of a combined ventilation system.This system integrates both exhaust and forcing ventilation ducts extending to the mouth of the blind heading.A significant innovation of this system is the prioritization of the exhaust fan over the blower fan.The efficacy of the proposed system has been evaluated both theoretically and experimentally.The theoretical analysis involved conducting 3D numerical simulations of dust-air distribution in a blind heading.The stationary turbulent flow of the air-dust mixture in the mine was calculated, taking into account the operating borer miner.The model's validity was confirmed against data from a full-scale experiment.A noticeable reduction in dust concentration was observed in the work areas of the borer miner and shuttle car when using the combined ventilation system compared to forcing ventilation.Based on these model findings, pilot tests of the effectiveness of the combined ventilation system were carried out in a real heading of a potash mine.They showed a reduction in dust concentration by 40-52% compared to the original version of the forcing ventilation system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".