Knock Prediction Using a Simple Model for Ignition Delay
Why this work is in the frame
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Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">An earlier paper has shown the ability to predict the phasing of knock onset in a gasoline PFI engine using a simple ignition delay equation for an appropriate surrogate fuel made up of toluene and PRF (TPRF). The applicability of this approach is confirmed in this paper in a different engine using five different fuels of differing <i>RON</i>, sensitivity, and composition - including ethanol blends. An Arrhenius type equation with a pressure correction for ignition delay can be found from interpolation of previously published data for any gasoline if its <i>RON</i> and sensitivity are known. Then, if the pressure and temperature in the unburned gas can be estimated or measured, the Livengood-Wu integral can be estimated as a function of crank angle to predict the occurrence of knock. Experiments in a single cylinder DISI engine over a wide operating range confirm that this simple approach can predict knock very accurately. The data presented should enable engineers to study knock or other auto-ignition phenomena e.g. in premixed compression ignition (PCI) engines without explicit chemical kinetic calculations.</div></div>
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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