Comparison of Three Evaporation Models Combined to the Distillation Curve Model for Multicomponent Fuel Droplet Evaporation
Bibliographic record
Abstract
The objective of this paper is to present a validation of the distillation curve (DC) model with experimental results. Along this validation, three different droplet heating and vaporization models are also compared to see how well they are able to predict the droplet change of diameter. As the DC model requires knowing the distillation curve of complex fuel, it is proposed to use a simplified distillation curve based only on the boiling range temperatures which is more easily known than the exact distillation curve of a given fuel. The simulation results with kerosene fuel show that models 1 and 2 show exactly the same droplet lifetime and temperature profiles under quiescent hot environment. However, the behavior is different when forced convection is present. The simplified DC model capture the general behavior of multicomponent fuel evaporation process. Finally, an experiment was conducted with a suspended droplet of gasoline and all three models show different temperature and diameter profiles.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".