Spray Combustion Characteristics and Gaseous Emissions of a Wood Derived Fast Pyrolysis Liquid-Ethanol Blend in a Pilot Stabilized Swirl Burner
Bibliographic record
Abstract
Biomass fast pyrolysis liquid (or bio-oil) is a cellulose based alternative fuel with the potential to displace fossil fuels in stationary heat and power applications. To better understand the combustion behavior and emissions of bio-oil, a 10 kW spray burner was designed and constructed. The effect of swirl, atomization quality, ignition source energy, air/fuel preheat, and equivalence ratio on the stability and emissions of bio-oil spray flames was investigated. A blend of 80% pyrolysis liquid and 20% ethanol by volume was used during the tests. Since the fuel is not fully distillable, it is important to have good atomization, thorough mixing, and increased recirculation to promote the burnout of nonvolatile material and decrease CO and hydrocarbon emissions. Air and fuel preheat are also important for reducing these emissions, although subsequent fuel boiling within the nozzle should be avoided in order to maintain flame stability. The amount of total primary air and atomizing air that can be used to improve turbulence, mixing, droplet burnout, and overall combustion quality is limited by the low volatility and tighter lean blow-out limit associated with bio-oil. The NO x produced in these flames is dominated by the conversion of fuel bound nitrogen. In order to reduce the NO x emissions without refining the fuel, the use of staged combustion is recommended.
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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".