Techno-economic assessment of underground mine dewatering systems
Bibliographic record
Abstract
To meet the global demand for minerals, Canada will need to develop new underground mines, deepen existing underground mines or convert open pit operations to underground mines. Dewatering systems will need to be implemented to handle the water encountered when going underground, which is typically generated from natural fissure water, rainfall ingress, rapid ice melts and mine service water. Many designers of operations, when designing their dewatering system, do not holistically look at the overall life of mine costs associated with said system. The Hydraulic Institute and Europump therefore developed a lifecycle cost (LCC) calculator in order to quantify all the associated costs. This paper will illustrate the use of the LCC calculator to conduct a techno-economic assessment of the three main dewatering systems as seen in industry, namely: cascading, single lift utilising in-line multistage pumps and opposed impeller multistage pumps. For each of the three systems, this paper will expand on the technology by way of their features, performance and maintenance requirements. For the purpose of this analysis, a theoretical underground mine with a pump station located 500 m below surface, and dewatering at a rate of 460.8 m³/h, was used. The results of the techno-economic assessment showed that a single-lift system utilising the opposed impeller configuration multistage pump technology has the lowest lifecycle cost over a 15-year period, which in turn resulted in the lowest rate per cubic metre dewatered.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| 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".