Modeling of a Heat-Integrated Biomass Downdraft Gasifier with Construction and Demolition Waste as Feedstock
Bibliographic record
Abstract
A mathematical model for heat-integrated downdraft gasification of pine wood is extended to account for construction and demolition (C&D) waste as feedstock. Model equations account for a high proportion of inerts in C&D waste compared to pine wood. Statistical subset selection is used to select 11 out of 39 parameters for estimation using 13 experimental runs. Model validation shows improved predictions compared to pine-wood parameters. Simulations reveal that a lower volumetric feed rate of C&D is required to generate the same energy as pine wood, due to its higher density. Using C&D results in lower H 2 /CO ratios and more tar in producer gas. An appropriate solid removal rate is crucial for higher-quality producer gas. Reducing the moisture of C&D from 8.1 to 5.0 wt % increases CO and H 2 mole fractions by 4.3 and 3.6%, respectively. Experimental and simulation results confirm that C&D is a promising feedstock for gasification and subsequent electricity generation.
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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 | 0.000 |
| 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) | 0.003 | 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".