Development and Validation of a Process Model To Describe Pyrolysis of Forestry Residues in an Auger Reactor
Bibliographic record
Abstract
In this study, a process model for an auger-style biomass pyrolysis reactor is developed to use as a tool in process optimization and scaleup. The plug-flow model for both solid and gas phases is assumed. A comparison between the kinetic models widely used in the literature to the experimental data was performed to determine the “best” kinetic model for our system. The transport equations for each phase are combined with the kinetic model to predict bio-oil, char, and non-condensable gas yields. The applied model was validated with experimental data from a 2–4 kg/h pilot-scale auger reactor. This reactor uses steel shot as a heat carrier and without carrier gas. The results show good agreement between experimental data and model prediction. The model was used to predict the yield of bio-oil as a function of the temperature, feed flow rate, and reactor pressure. These simulations indicate that the model is a useful tool in design and scaleup of auger-type pyrolysis reactors using a heat carrier.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".