An Investigation of Gasoline Engine Knock Limited Performance and the Effects of Hydrogen Enhancement
Bibliographic record
Abstract
A set of experiments was performed to investigate the effects of relative air-fuel ratio, inlet boost pressure, and compression ratio on engine knock behavior. Selected operating conditions were also examined with simulated hydrogen rich fuel reformate added to the gasoline-air intake mixture. For each operating condition knock limited spark advance was found for a range of octane numbers (ON) for two fuel types: primary reference fuels (PRFs), and toluene reference fuels (TRFs). A smaller set of experiments was also performed with unleaded test gasolines. A combustion phasing parameter based on the timing of 50% mass fraction burned, termed “combustion retard”, was used as it correlates well to engine performance. The combustion retard required to just avoid knock increases with relative air-fuel ratio for PRFs and decreases with air-fuel ratio for TRFs. PRFs, which require about 5° CA of combustion retard per bar of net indicated mean effective pressure (NIMEP), need about three times as much combustion retard as TRFs when boosted to achieve the same NIMEP. Both fuel types require an average of about 3° CA of combustion retard per unit of increased compression ratio. The trends for gasoline are about halfway between PRF and TRF trends. An end-gas model that employs detailed chemical kinetics and experimental cylinder pressure data successfully approximated the response of PRFs and TRFs to compression ratio, air-fuel ratio and boost. Adding gasoline reformate (a mixture of H2, CO, and N2) decreases the combustion retard required to avoid knock by about 2° CA per 3% fuel reformed fraction for PRFs. For TRFs with low alkane content reformate addition is less effective. Reforming up to 30% of the fuel entering an engine allows increased compression ratio or increased turbocharging without increasing combustion retard. A simplified analysis suggests that increasing compression ratio and downsizing the engine to maintain constant maximum brake torque would increase brake fuel efficiency by about 9%. Turbocharging and downsizing would increase efficiency by about 16%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.002 | 0.001 |
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".