Extending the Lean Limit of Natural-Gas Engines
Why this work is in the frame
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Bibliographic record
Abstract
Two different methods to improve the thermal efficiency and reduce the emissions from lean-burn natural-gas fueled engines have been developed and are described in this paper. One method used a “squish-jet” combustion chamber designed specifically to enhance turbulence generation, while the second method provided a partially stratified-charge mixture near the spark plug in order to enhance the ignition of lean mixtures of natural gas and air. The squish-jet combustion chamber was found to reduce brake specific fuel consumption by up to 4.8% in a Ricardo Hydra engine, while the NOx efficiency trade-off was greatly improved in a Cummins L-10 engine. The partially stratified-charge combustion system extended the lean limit of operation in the Ricardo Hydra by some 10%, resulting in a 64% reduction in NOx emissions at the lean limit of operation. Both techniques were also shown to be effective in increasing the stability of combustion, thereby reducing cyclic variations in cylinder pressure.
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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 | 0.001 |
| 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 | 0.000 | 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