A computational model for temperature and sterility distributions in a pilot‐scale high‐pressure high‐temperature process
Bibliographic record
Abstract
Abstract High pressure high temperature processing is a candidate food sterilization process in which heat is generated volumetrically within the food as a result of rapid pressurization to 600 MPa or higher. For commercial viability the temperature profile in the process should be as uniform as possible. A model has been developed to predict the flow and temperature fields inside a pilot scale (35 L) vessel during the pressure heating, holding and cooling stages of the process. Simulations on the empty vessel show that thermal conduction causes excessive cooling. The model agrees well with experimental results in which thermocouples are used to measure temperature throughout a metallic composite carrier inserted into the vessel. The model is used to design a Polytetrafluoroethylene (PTFE) carrier which produces thermal uniformity within the carrier. Predicted variations of sterility resulting from a process are produced using the F0‐value distribution. No significant reduction of spores was seen in the empty vessel, while more than 94.6% of the PTFE carrier volume achieved a reduction greater than 1012. © 2007 American Institute of Chemical Engineers AIChE J, 2007
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".