Auto‐thermal combustion of lean gaseous fuels utilizing a recuperative annular double‐layer catalytic converter
Bibliographic record
Abstract
Abstract The results of the investigations on the auto‐thermal combustion of lean gaseous fuels in a recuperative annular double‐layer catalytic converter were reported in the current contribution. Several modifications were proposed to improve the stationary and transient behaviour of the converters. The miniaturized recuperative converter exhibited reduced resistances to the mass and heat transfer and attractive bifurcation changes of a very low combustible content, that is, the histeresis for Tin and Cin and isola for mfin and hg. It was revealed that the utilization of an adiabatic recuperative converter led to an autothermal operation for Tin = 300 K and Cin = 177 ppmv of propane. The inlet fuel mass flow rate range to apply was wider than earlier reported in the literature, that is, 0.63–2.94 × 10−6 kg s−1 for Cin = 200 ppmv. Transient experiments showed that recuperative converter was able to transfer short‐time inlet disturbances of parameters due to the energy accumulation and temporal reversed recuperation counteracting to extinction or to destructive overheating of the catalysts. Stability analysis was performed showing location of folds, stable and unstable branches of solutions for the different parameters of the recuperative converter. A two‐dimensional process model was developed.
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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) | 0.000 | 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 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".