Computer Integrated Manufacturing of Polyurethane Foams Steered by Measured and Calculated Data in Comparison
Bibliographic record
Abstract
Polyurethane foams were manufactured under continuous measurements of isocyanate content, temperature, expansion and viscosity. Parallel model calculations were executed based on the driving force of 50kJ/mole heat of reaction of the energy rich isocyanate group and on thermodynamic balances of weight and heat of formation as well as on a kinetic model using a first order reaction for the isocyanate consumption and a relation for the viscosity dependent on conversion and on a viscosity constant. The agreement between continuous measured and calculated data was satisfying. The parameters isocyanate content, temperature, expansion and viscosity controlled and steered the variables of the production plant, like dosage of components, temperature and conveyer speed. The kinetic model was also valid for polyurethane foams with additives, which did not react with components of foam, like flame retardants or pigments. The thermodynamic balances of weight and heat predicted residues and consumed heats by degradation under fire, which correlated with those measured by TGA and DSC. The target was to establish computer integrated manufacturing without continuous measurements but by mere model calculation. This was possible with the knowledge of the first order velocity constant and the viscosity constant.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".