Diesel-fired boiler performance and emissions measurements using a combination of diesel and palm biodiesel
Bibliographic record
Abstract
Biodiesel is widely accepted as a fuel that is similar to diesel with various advantages. Biodiesel's low-temperature flow qualities are one of its characteristics that limits its use. The goal of this study was to see how volumetric blends of palm biodiesel and diesel, and diesel as a fuel affected the performance and emissions characteristics of a diesel fired vertical coil type, water tube, and non IBR boiler. Various volumetric blends were prepared like PB25, PB50, PB75, PB100 and test in diesel fired boiler with variation in injection pressure. Performance of PB25, PB50, PB75, and PB100 fuels was observed 62.73%, 62.45%, 62.36%, and 62.32%, respectively, compare to pure diesel the value of all blends is either slightly higher or comparative. The maximum boiler efficiency with B100 fuel is 64.98%, which is lower than the pure diesel as fuel 65.30%. Because B100 has a higher kinematic viscosity, it has a larger droplet diameter which lead to poor spray formation and thus a lower boiler efficiency. At 11 bar fuel injection pressure, maximum EGT for diesel, PB25, PB50, PB75, and PB100 fuels is 300 °C, 295 °C, 308 °C, 328 °C, and 340 °C, respectively. Other blends, with the exception of B25, have higher EGT than diesel fuel. At a same fuel injection pressure of 11 bar, CO emissions from diesel, B25, B50, B75, and pure palm biodiesel fuels are 0.037%/Vol., 0.0336%/Vol., 0.0326%/Vol., 0.033%/Vol., and 0.036%/Vol., respectively. CO emissions for PB50 are the lowest of all the fuels tested, followed by B25, diesel, and B100. CO emissions from diesel, PB25, PB50, PB75, and PB100 fuels at maximum fuel pressure are 0.0605%/Vol., 0.0616%/Vol., 0.0605%/Vol., 0.060%/Vol., and 0.05%/Vol., respectively. When compared to diesel fuel, CO emissions from B100 fuel are 21% higher. The highest HC emissions are 18 ppm, 16 ppm, 14 ppm, 13 ppm, and 12 ppm for diesel, PB25, PB50, PB75, and PB100 fuel, respectively. When utilizing B100 fuel, HC emissions are reduced by around half compared to when using diesel fuel.
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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 | 0.000 | 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) | 0.001 | 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".