Microwave Dewatering of Gibbsite-Type Bauxite Ores: Permittivities, Heating Behavior and Strength Indices
Bibliographic record
Abstract
Microwave radiation is a relatively new energy source that is being considered for several applications in mineral processing and extractive metallurgy. In the present research, various gibbsite-type bauxite ores were subjected to microwave radiation. The main objective was to assess the effect of microwave dewatering on the compressive strength indices of the ores and to compare the results obtained to those for conventional heating. Firstly, the fundamental interactions of the microwaves with the ores were evaluated by determining both the real and the imaginary permittivities as a function of temperature, and these were related to the water content. Secondly, the microwave heating behavior was modeled using a 24 factorial statistical analysis. Thirdly, the effect of dewatering by microwave heating on the compressive strength indices of roughly spherical bauxite ore pisoids was studied, and these results were compared to those obtained using conventional heating. Fourthly, the effect of particle size on the compressive strengths of irregular-shaped single particles of bauxite ore was investigated using both heating techniques. Finally, the energy requirements for dewatering of the ores, and hence reducing their compressive strengths, were compared for both processes. On the laboratory scale, the results showed that in comparison to conventional dewatering, microwave dewatering resulted in lower strength indices at both lower moisture removals and energy inputs.
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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 | 0.000 |
| 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 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".