An Analysis of the Ambient Condition Effect on Biodiesel Spray Using Constant Volume Chamber
Bibliographic record
Abstract
Diesel engines are high compression ignition engine which are now very vastly used for heavy vehicles and machineries. Diesel fuel is compressed under the right condition to ignite inside the constant volume chamber. Researchers have been studying for many years on ways to increase the efficiency of diesel engine as well as reduce the emission. The main idea of this research is to understand the effect of temperature on the spray characteristics, as well as fuel-air mixing characteristics. These are the characteristics responsible for ignition of diesel sprays. This research is first conducted by investigating the influence of biodiesel properties and ambient condition on the mixture formation especially at early stage of fuel-air premixing. This research was continued with injecting diesel fuel into the chamber using a Bosch common rail system. Direct photography technique with a digital camera was used to capture the real images of spray evaporation, spray length, and mixture formation with the time changes. The values of the temperature were recorded at ambient temperature, 55°C, 70°C, 85°C as well as 100°C. Injection pressure of 0.1 MPa up to 0.7 MPa was induced into the chamber with an increment of 0.1 MPa. The condition to which the fuel is affected was estimated by combining information on the block temperature, ambient temperature and photographs of the spray. The increase in block temperature increases the ambient temperature inside the chamber resulting in gain of spray area and wider spray angle. Thus predominantly promotes for a better fuel-air mixing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".