Combustion of Corn Stover Bales in a Small 146-kW Boiler
Bibliographic record
Abstract
Spring harvested corn stover was used for direct combustion in a 146 kW dual chamber boiler designed for wood logs. Stover had a very low moisture content (6.83 ± 0.17%), a gross calorific value (GCV) of 18.57 MJ/kg of dry matter (±0.32 MJ/kg DM) and an ash content of 5.88% (±1.15%). Small stover bales (8.83 ± 0.90 kg) were placed manually in the upper combustion chamber at a rate of 10.5 to 12.8 kg/h over a 24-h period, with three replications, and compared to a control wood combustion trial (12.1 kg/h during 24 h). The overall heat transfer efficiency for stover was lower than for wood (57% vs. 77%). Stover bales produced on average 7.5% ash which included about 2% of unburned residues while wood produced 1.7% ash. CO gas emissions averaged 1324 mg/m³ for stover (118 mg/m³ for wood). The corn stover showed a good calorific potential, but it would have to be densified and the boiler should be modified to improve airflow, completeness of combustion and handling of the large amount of ash formed.
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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".