Advancing Industrial Smokeless Flaring: Experimental Study into a Swirl Air-Assist Burner
Bibliographic record
Abstract
The performance of a prototype swirl air-assist burner, designed to suppress flame thermal radiation and improve flame stability in crosswinds for industrial smokeless flaring, was experimentally investigated.The burner features a central swirl core shaped like a diffuser, equipped with tangential swirl blades to promote mixing between fuel and air.It was tested using vapour propane at assistair-to-fuel ratios (AAFRs) ranging from about 29 to 80, which gradually led to the formation of a central recirculation region.Visible flame characteristics were recorded with a video camera, while thermal radiation properties-including emissive power and emissivitywere measured using an infrared camera.Increasing the AAFR reduced the flame's height-to-width ratio, thereby enhancing flame stability under crosswind conditions.Smoke production also diminished, transitioning from a heavily smoky flame to a cleaner one.As the AAFR increased from 0 to its maximum value, the flame area (m²) and emissive power (W/m²) decreased by 69% and 24%, respectively.Overall, the experimental results confirm the suitability of this swirl air-assist burner design for industrial smokeless flaring, demonstrating improved performance in stabilizing the flame under crosswind conditions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".