Evaporation Time of Gasoline and Diesel Fuel Droplets on a Hot Plate: The Influence of Fuel Deposits
Bibliographic record
Abstract
The objective of this paper is to present experimental results of multicomponent fuel droplets impinging on a hot surface in order to quantify the influence of fuel build-up deposits on the evaporation time. The experiments were conducted with gasoline and diesel fuels to first obtain curves of evaporation time as a function of plate temperature. Based on these curves the Nukiyama and Leindenfrost temperatures were identified. In a second step, the effect of fuel deposit on the droplet evaporation time was studied. Based on the above evaporation time curves, plate temperatures were chosen as to offer a similar evaporation time but at temperatures below and above the Nukiyama and Leindenfrost temperatures respectively. This was done in order to isolate the effect of fuel deposits from the different evaporation mechanisms. The evaporation of successive impinging droplets was then measured. The results hence obtained indeed showed that the fuel deposit has a different impact on the evaporation time according the evaporating mechanism or equivalently the plate temperature. For plate temperatures lower than the Nukiyama temperature, gasoline and diesel fuel droplets showed an increase of their evaporation time as the amount of successive impinging droplets increased. The trend was reversed for plate temperatures above the Leindenfrost temperature. A hypothesis for this latter case is that the fuel deposit disrupts the vapor layer supporting the droplet and therefore provides a greater heat flux to the evaporating droplet. Finally, droplet evaporation times as a function of plate temperature were measured with an initial fuel deposit covering the plate. These results in turn showed that the global thermal diffusivity and porosity of the surface are changed by the presence of the fuel deposit. The consequence of these property changes are then shown to have a direct and global impact on the fuel evaporation time curves.
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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 | 0.000 |
| 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".