A real‐time light‐scattering technique for tailings solids measurement
Bibliographic record
Abstract
Abstract This study presents the concept of an economic in situ light‐scattering sensor for real‐time measurement of the solid content in tailings facilities. An experimental setup using a blue (405 nm wavelength) laser diode and silicon photodiodes was constructed to measure the angular distribution of the intensity of scattered light. It was found that the angular intensity of scattered light for tailing samples follows a cos n (θ) relation with n ≈ 1.5, where θ is the angle between the laser beam and the photodiode. An angular value of θ = 20° was chosen for the sensor design based on a high signal‐to‐noise ratio. The setup was used to determine the relation between scattered light intensity and solids content using a thickened tailings underflow from an oil sands facility and Kaolin as a model material. It was observed that the intensity of scattered light tends to increase with an increase in solids content, with qualitatively similar settling behavior for the two materials but at largely different time scales. An insertion‐based prototype was built and tested in a large (2.7 m height) settling column with treated mature fine tailings, and the light‐scattering data were verified by standard gravimetric method and gamma‐ray measurements. In general, good agreement was established between these measurements in the absence of optical fouling, which demonstrates the potential of the sensor as an effective tool for tailings management.
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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 | 0.001 | 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".