Bibliographic record
Abstract
Comminution and classification circuits consume significant amounts of energy. Some estimates show that\ncomminution processes accounts for around 40 % of the total energy consumed in mining operations and 1.5-1.8 % of the\ntotal national energy consumption in mining intensive countries such as South Africa, Australia and Canada (Tromans, 2008).\nApart from recent market fluctuations the global trend is that the demand for metals and minerals is increasing (Norgate and\nHaque, 2010). At the same time the ore competence generally increases as material is mined at greater depths and the grade is\nusually lower. The consequence is that increased amounts of raw material need to be processed in larger and larger\ncomminution devices. The task of reducing the energy consumption in this context seems daunting.\nThe conventional comminution circuit is usually based on a crushing and screening process followed by a tumbling milling\nprocess. HPGR machines and other new devices have also become more common during the last 20 years. Independent of\nwhat type on units that are used in the circuits the global trend is that larger and larger comminution devices are manufactured\nand installed.\nWith this outlook as a foundation we propose an alternative mindset to think about circuits; poly-stream comminution circuits.\nA general trend in product development is that technologies transform from mono-systems to poly-systems. In this paper the\nconcept is described and exemplified in a case study including a comparison with a conventional SABC circuit. In poly-stream\ncircuits the material streams after one or several parallel primary crushing stages are split into 5-20 streams by using ore sorting\nand classification units. Each stream handles a proportional throughput capacity and the material passes through a dedicated\nset of smaller comminution and classification modular units with settings optimized to target the specific properties of the\nmaterial in each stream.\nThe results of this conceptual case study suggests that smaller, instead of larger, comminution and classification units open up\nfor modularization, higher theoretical operational availability, better plant flexibility and expansion potential. Lower mass flow\nstreams enable the use of ore sorting with separate treatment and early rejection of gangue. It is generally also easier to achieve\nhigher energy efficiency performance for smaller comminution, classification and separation units.\nThere are a number of apparent challenges and problems associated with the concept. It requires new solutions for stream rerouting,\nsensor technology, advance control systems and advanced maintenance management systems to name a few. However,\nthe consequent conclusion of this hypothetical concept is that perhaps the focus of research and development efforts should\ntarget material handling, sensor technology and comminution unit modularization in order to meet the challenges of future\ncomminution circuits.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.008 |
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".