Відновлюване дизельне паливо для автомобільного транспорту: моделювання випаровування
Bibliographic record
Abstract
The construction of a plant for the production of green hydrogen in Ukraine by the Ukrainian company «Hydrogen Ukraine», in the city of Reni, near Odessa, adds optimism about the use of hydrogen as a fuel for road transport. But on the other hand, a lot of cars that have already been in use and run on diesel fuel are imported to Ukraine from Europe. The high emissions of nitrogen oxides that these vehicles have when using diesel fuel have led to a ban on their use in Europe. But a good solution for Ukraine may be to replace diesel fuels with other alternative fuels, such as renewable fuels. Replacing traditional fuels in the transport sector is a major challenge, as any alternative fuel must provide comparable energy density. Renewable fuels such as renewable diesel (also known as green diesel and hydrotreated vegetable oil) are particularly suitable for this purpose, as they have significant advantages over other alternative fuels, necessitating modifications to the existing fleet of internal combustion engines. Renewable diesel is already used in road transport as a substitute for diesel fuel in the USA, Sweden, Finland, Canada, etc. countries of the world. Renewable diesel has some differences from fossil diesel, such as lower density, higher flash point, reduced evaporation losses and slightly increased viscosity. The purpose of this work is to simulate the evaporation of renewable diesel for road transport. For this purpose, the physical properties of renewable diesel in comparison with diesel fuel were analyzed. The most common peaks in the studied RD were in the range of n-C17 to n-C18, and almost all components ended in n-C18. Simulation of evaporation of biodiesel and renewable diesel fuel was performed. It was assumed that the droplet, which had an initial temperature of 360 K, moved under stationary conditions at a speed of 10 m/s. The initial radius of the droplet was assumed to be equal to 12.66 μm. The ambient temperature and pressure were assumed to be constant at 800 K and 30 bar, respectively. The simulations showed a shorter lifetime of droplets from biodiesel and also renewable diesel compared to diesel fuels. The evaporation of renewable fuel droplets will depend on the composition of that fuel, so it is important to know the composition of the renewable fuel to modelling the evaporation process.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".