Experimental Investigation of Heat Transfer in Stagnant Bed for Processing of Agriculture Products
Bibliographic record
Abstract
The paper deals with the heat transfer associated with processing of agriculture products.Granular materials such as legumes or cereals often require preheating to certain temperature for its processing.This can be secured by heat exchanger, where it is necessary to have a knowledge about heated material behaviour for technically and economically proper design.Commonly used construction type of heat exchangers for the food processing is a platen heat exchanger.Thus, the heat transfer coefficients between the planar heated surface and the stagnant bed are main subject of this paper.Heat transfer is theoretically described based on the penetration model that considers the bed of particles as one continuous phase.For experimental investigation of heat transfer, a stand for heating a packed bed of material was designed and manufactured.Selected materials were experimentally measured at different levels of heating temperature to gain the time dependence of the heat transfer coefficients and the temperature distribution in the bed of material.The temperature in the bed of material rapidly increases at area close to the heating surface, while at a greater distance a temperature increase is very small even after 30 min.The temperature increases faster in material with the lower specific heat capacity.The heat transfer coefficient is not affected by heating temperature but only by the change of material properties.In agreement with both experimental and theoretical results, the heat transfer coefficient decreases significantly at the time of heating.The most intense heat transfer occurs in the first heating phase (in the order of a few minutes), after which the heat transfer is stabilized and lowered.These results may be used for designing the mentioned application of heat exchangers.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".