Economic trends for temperature of sugarcane bagasse pyrolysis
Bibliographic record
Abstract
Abstract This work examines some aspects of sugarcane bagasse pyrolysis. Fixed bed pyrolysis was performed varying the final process temperature. Product yields and the variation of quality properties (calorific values) of bio‐oil, biochar, and non‐condensable gas were investigated. A mathematical model to simulate the trend of temperature that maximizes a marginal gain was developed considering the regression equations for yields and prices of products (related to market prices and calorific value of conventional fuels) and for the amount of biomass used to supply energy to the process. Two methodologies were adopted to calculate the optimum process temperature. The results showed very close temperatures (600 and 602 °C) for the best performing simulations of endogenous and fixed prices methods, with little difference between the yields of products, but with good variation between the marginal gains ($124.9/tonne and $129.8/tonne). Finally, the results of endogenous prices method for the fixed bed reactor were compared to the vacuum and fast pyrolysis reactors.
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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 | 0.001 | 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".