Characterization of Emissions from Diffusion Flare Systems
Why this work is in the frame
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Bibliographic record
Abstract
Emissions from flares typical of those found at oil-field battery sites in Alberta, Canada, were investigated to determine the degree to which the flared gases were burned and to characterize the products of combustion in the emissions. The study consisted of laboratory, pilot-scale, and field-scale investigations. Combustion of all hydrocarbon fuels in both laboratory and pilot-scale tests produced a complex variety of hydrocarbon products within the flame, primarily by pyrolytic reactions. Acetylene, eth-ylene, benzene, styrene, ethynyl benzene, and naphthalene were some of the major constituents produced by conversion of more than 10% of the methane within the flames. The majority of the hydrocarbons produced within the flames of pure gas fuels were effectively destroyed in the outer combustion zone, resulting in combustion efficiencies greater than 98% as measured in the emissions. The addition of liquid hydrocarbon fuels or condensates to pure gas streams had the largest effect on impairing the ability of the resulting flame to destroy the pyrolytically produced hydrocarbons, as well as the original hydrocarbon fuels directed to the flare. Crosswinds were also found to reduce the combustion efficiency (CE) of the co-flowing gas/condensate flames by causing more unburned fuel and the pyrolytically produced hydrocarbons to escape into the emissions. Flaring of solution gas at oil-field battery sites was found to burn with an efficiency of 62-82%, depending on either how much fuel was directed to flare or how much liquid hydrocarbon was in the knockout drum. Benzene, styrene, ethynyl benzene, ethynyl-methyl benzenes, toluene, xylenes, acenaphthalene, biphenyl, and fluorene were, in most cases, the most abundant compounds found in any of the emissions examined in the field flare testing. The emissions from sour solution gas flaring also contained reduced sulfur compounds and thiophenes.
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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 it