Comparison of the Spray Combustion Characteristics and Emissions of a Wood-Derived Fast Pyrolysis Liquid-Ethanol Blend with Number 2 and Number 4 Fuel Oils in a Pilot-Stabilized Swirl Burner
Bibliographic record
Abstract
Biomass fast pyrolysis liquid (bio-oil) is a cellulose-based alternative fuel with the potential to displace fossil fuels in stationary heat and power applications. To 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 (pilot) energy, and total primary combustion air 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, and the results were compared to the burner operation with number 2 and number 4 fuel oils. Bio-oil exhibits higher emissions than number 2 fuel oil at any given operating point. This is primarily due to better atomization quality with number 2 fuel oil, although not as a consequence of viscosity differences, which are minor at the measured fuel temperature in the nozzle (>80 °C). The disparity in atomization quality is caused by differences in the relative amount of atomizing air to liquid fuel flow rate provided to the nozzle at a fixed energy throughput. Another factor that contributes to higher bio-oil blend emissions is worse overall distillation characteristics compared to number 2 fuel oil. As a fully distillable fuel that evaporates high-energy compounds, number 2 fuel oil is far less sensitive to changes in flame stability or blow-off brought upon by varying the swirl number, atomizing air, pilot energy, or primary combustion air flow rate. Because of a combination of these atomization quality and fuel volatility effects, the bio-oil blend cannot operate over as wide of a range of primary air or atomizing air flow rates as number 2 fuel oil. The bio-oil blend has a lower boiling point than diesel and is much more susceptible to flashing-induced combustion instabilities, which lead to intermittent blow-out and higher CO emissions. The NO x and particulate emissions of number 2 fuel oil are lower than bio-oil because of the negligible fuel nitrogen and ash contents in the fuel, respectively. Number 4 fuel oil is more comparable to bio-oil because of its nondistillable fraction, fuel nitrogen, and ash contents. CO and hydrocarbon emissions are lower than the bio-oil blend, but total particulates and carbonaceous residues are higher for number 4 fuel oil. This is despite better atomization and a lower nondistillable fraction, suggesting that the fuel-oil residues are more difficult to burn out completely. Fuel NO x conversion efficency of number 4 fuel oil is similar to the bio-oil blend. There are differences in fly ash mineral composition between the two fuels, as well as a much higher sulfur content for number 4 fuel oil. Carbon burnout analysis indicates that all fuels can achieve high carbon conversion efficiency (>99%) at the best operating conditions. The bio-oil blend has the highest amount of unburned carbon, of which the majority is in the form of gaseous CO.
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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".