Performance of Auto-Cyclic Reactor in Catalytic Combustion of Lean Fuel Mixtures
Bibliographic record
Abstract
This work examines the experimental assessment of the conditions required for sustainable autothermal catalytic combustion of mixtures of lean fuels (methyl ethyl ketone (MEK), acetone, propane, and methane) in a small nonadiabatic laboratory auto-cyclic reactor (ACR) loaded with a combination of laboratory-prepared monoliths and commercial palladium catalyst pellets. Despite the non-optimized physical parameters of this reactor, the experiments demonstrated that, for a given fuel, the domain of autothermal operation is dependent primarily on fuel/catalyst reactivity that, in turn, dictates the minimum heat output (power) requirement of the air/fuel mixture and, to a lesser degree, flow rate. In correlation with the reactivity of individual fuels, the power requirement for a flow rate of 64 L/min (ambient) increased, from 375 W for MEK and acetone to ∼480 W for propane and 613 W for methane. For propane and methane combusted under the limiting conditions, oscillatory behavior was observed with the periods that correlated with the power of the fuel/air mixture. When the methane/air feed mixture was heated to 400 °C before entering the ACR, sustained combustion was assured for 0.6% methane flowing at a rate of 97.2 L/min.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".