Numerical Investigation of Spray Characteristics of Diesel Alternative Fuels
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">Due to increasingly strict emission regulations for IC engines, there is a significant motivation to investigate the relevant physical processes with the objective to reduce the reduction of exhaust gas emissions. Spray characteristics play a progressively important role in the consequent processes of mixture formation, ignition, combustion and pollutant formation in direct injection diesel engines. It is also important to develop an understanding of the atomization qualities of alternative fuels such as Biodiesel fuels as potential substitutions for conventional diesel fuel. In this research, the effect of injection and ambient parameters on spray breakup and atomization of different alternative fuels are investigated using CFD simulation. An Eulerian-Lagrangian approach is implemented in order to study the interaction of the continuous and discrete phases. Numerical simulations are extensively validated via experimental data available in literature for a constant volume chamber under ultra-high injection conditions up to 300 MPa. Simulated spray tip penetration, spray cone angle and spray images are compared with experiments and analytical correlations for three fuel types (diesel, palm oil, cooked oil), three injection pressures (100, 200, 300 MPa), and two ambient densities (15, 30 kg/m₃). Effect of mesh structure and two breakup models (WAVE and KHRT) on spray penetration were also investigated. Particle size distribution in radial and axial directions was studied.</div></div>
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 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".