Planar laser-induced fluorescence of nitric oxide in isomeric butanol and butane stagnation flames
Bibliographic record
Abstract
The significant efforts to reduce global fossil fuel dependence have led to the development of biofuels as an alternative. Despite their growing significance, alcohol biofuels still require fundamental study, particularly in the area of NOx emissions. Planar laser-induced fluorescence (PLIF) was used to obtain nitric oxide (NO) production profiles from stagnation flames of premixed n- and iso-butanol; n- and iso-butane flames were also measured to offer context with alkane fuels. PLIF measurements were corrected for laser sheet variations and non-radiative quenching by signalpost-processing and quantified with a NO-seeding calibration method. Particle-image velocimetry (PIV) was performed to characterize the centreline velocity of the experimental flow which was then used for chemical kinetic simulations of the experiment. Simulations were performed for n-butanol and n-butane flames with a combined NOxsubmechanism. Experimentally, butanol fuels were found to produce significantly less NO than butane fuels overall. Although both models accurately predict the production of NO in the post-flame region, there is a disparity in NO production occuring in theflame zone via the prompt-NO pathway, suggesting that the chemical kinetics in the mechanisms require modification. The n-butanol simulation shows poor agreement at all tested equivalence ratios, while n-butane performed poorly for the rich case. This study offers new experimental data to aid in further improvements in kinetic modelling of butanol and butane combustion, and NOx formation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".