Measuring Moisture Content of Potash Bulk Fertilizers Using a Steel Ball in a Transient Heat Transfer Process
Bibliographic record
Abstract
This research measures the effective thermal conductivity of a bed of granular potash particles and determines its relationship to moisture content by measuring the time dependent temperature of a heated steel spherical ball inserted into the bed. In these tests, the steel ball is heated to 5−10 °C above the bed temperature and then placed into the bed. As the heat diffuses throughout the bed, a data acquisition system records the temperature of the ball. The bed effective thermal conductivity is then calculated from these data. Tests were performed for five different ranges of particle sizes at five moisture contents (i.e., 0, 0.25, 0.5, 1.0, 2.0, and 3.0 wt %). The coefficient of determination for a linear fit between moisture content and effective thermal conductivity was found to vary from 0.913 to 0.998. This technique is expected to be practical for field measurements with granular materials, such as bulk fertilizers, because data can taken at selected points in the bed and because of its low cost, quick response, and simplicity of instrumentation.
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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 | 0.000 | 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".