Predictive Kinetics Model for an Industrial Waste Tire Pyrolysis Process
Bibliographic record
Abstract
A new pyrolysis model was developed to predict the individual product (noncondensable volatiles, condensable volatiles, and char) yield for Ecolomondo’s industrial waste tire pyrolysis process. This novel predictive kinetics-based model couples product selectivity data obtained from thermogravimetric analysis experiments to a global single-step decomposition reaction term to reproduce the nonlinear relationship between product selectivity and temperature. A transient energy balance based on a lumped capacitance method was also used to calculate the tire shred temperature using the rotary drum wall temperature as an input. The kinetics model was compared to experimental oil production data from the industrial process as well as existing models in the literature. It is shown that the model can successfully predict the oil production of the industrial process and the model accuracy is greater for smooth operating conditions. On the other hand, other pyrolysis models from the literature failed to accurately predict the oil production.
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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 | 0.000 | 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".