Experimental Study of Turbulent Burning Velocity of Premixed Biogas Flame
Bibliographic record
Abstract
Biogas is a renewable source of energy produced by anaerobic digestion of organic material and composed mainly of methane (CH4) and carbon dioxide (CO2). Despite its lower heating value, biogas can still replace fossil fuels in several engineering stationary power generation and other industrial applications. Although numerous published studies were devoted to advance our understating of biogas combustion, experimental data of some parameters such as turbulent burning velocity (St) under certain operating conditions is still lacking. The present study aims to experimentally determine biogas turbulent burning velocity under normal temperature and pressure conditions. Turbulent premixed biogas–air flame was ignited at the center of a 29 L fan-stirred spherical combustion chamber of nearly homogeneous and isotropic turbulence. Test conditions consisted of varying turbulence intensity and biogas surrogate composition. Outwardly propagating biogas flames were tracked and imaged using Schlieren imaging technique. The results showed that, by increasing turbulence and reducing methane percentage in the surrogate, the flammability of the mixture shrinked. In addition, the curve fits of biogas turbulent burning velocity versus the equivalence ratio exhibited two different trends. The peak of turbulent burning velocity shifted away from nearly lean equivalence ratio toward the stoichiometric at a fixed turbulence intensity and higher CH4 percentage in the surrogate. However, for the same biogas surrogate composition, the peak of turbulent burning velocity shifted away from stoichiometric toward leaner equivalence ratio with increased turbulence intensity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".