Bibliographic record
Abstract
The combustion of wood processing residues was tested in the 0.8 MWth CANMET Circulating Fluidized Bed Combustor (CFBC) pilot plant. The specific residues tested were three different types of coniferous tree bark (i.e. from different locations to represent a range of possible fuels and fuel properties). Combustion conditions may be summarized as follows: fuel moisture levels 42–60%, fluidizing velocity 2.1–2.4 m/s; bed temperature 785–910 °C; maximum freeboard temperature 980–1070 °C and excess air levels 20–75%. The CFBC unit was able to burn the high moisture level fuels with no detrimental effect. In all trials the residues burned very well, with combustion efficiency greater than 99% based on overhead carbon loss. Emissions measurements were made of the following pollutant species CO, NOx, N2O, SO2, and dioxins and furans. The emissions levels were: 100–130 ppm NOx; <1 ppm N2O; 5–20 ppm SO2 and 400–1800 ppm CO. These emission levels are well below pollution guidelines for all major pollutants except CO. This however can be traced to the non-homogeneous nature of the coarse feed in the pilot plant. The problem can reasonably be addressed in a full-scale unit by a more stable feed system. A preliminary economic analysis of a new 25 MW FBC power plant firing these fuels was performed. Conservative inputs give a cost of 6 cents/kWh for the electricity produced and a economic wood haulage radius of 70 km.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".