An Optically-Accessible Combustion Apparatus for Direct-Injection Natural Gas Ignition Studies
Bibliographic record
Abstract
Research investigating direct injection natural gas (DING) diesel engines shows many attractions in engine performance including higher thermal efficiency and higher power output as well as significant improvement of exhaust emissions. However, ignition of injected natural gas is difficult and requires some form of ignition assist, such as a diesel pilot or a glow plug. This paper introduces the experimental apparatus used for compression ignition engine studies in the Engine Research and Development Laboratory (ERDL) at University of Toronto. The apparatus consists of an optically accessible constant volume combustion bomb coupled to a single-cylinder Cooperative Fuel Research (CFR) engine through its spark plug port. The engine provides rapid compression to create realistic engine conditions in the combustion bomb and also scavenges the combustion products. During the engine compression process, the piston pushes the air from the engine cylinder to the constant volume combustion bomb, generating high-pressure, high-temperature initial conditions and a strong swirling air flow in the constant volume combustion bomb. Experiments were conducted to measure temperatures and pressures in the constant volume combustion bomb for a range of initial conditions. The experiments were complemented by numerically modeling the whole domain of the CFR engine cylinder, the constant volume combustion bomb, and the port connecting them using a modified KIVA-3V code. The code computes spatially and temporally resolved pressure, temperature and swirl intensity in the constant volume combustion bomb during the compression process. The experimental and the numerical results are in satisfactory agreement and provide validation of the initial conditions in the constant volume combustion bomb for subsequent studies of injection and ignition.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| 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 teacher head, 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".