PERFORMANCE AND ENERGY BALANCE OF A LOW HEAT REJECTION DIESEL ENGINE OPERATED WITH DIESEL FUEL AND ETHANOL BLEND
Bibliographic record
Abstract
In this study, it was aimed to investigate the effect of ceramic coating on a turbocharged diesel engine performance and energy balance. For this purpose, cylinder head, valves and pistons of the engine were coated with yttria stabilized zirconia layer with a thickness of 0.35 mm nickel-chromium- aluminium bond coat, as well as the atmospheric plasma spray coating method with a thickness of 0.15 mm. Then, the engines were tested for full load. The heating values of the diesel fuel and ethanol were 46.2 and 25.182 MJ/kg, respectively. Because of the lower heating values of the ethanol, compared with the diesel fuel, it appears to have lower following to engine power, torque and SFC. Compare to engine power of SDE, LHRe has increased about 2%, LHReth has decreased about 22% at all engine speed. Compare to engine torque of SDE, LHRe has increased about 2.5%, LHReth has decreased about 23 % at all engine speeds. Compare to SFC of SDE, LHRe has decreased about 1.1 %, LHReth has increased about 54 % at all engine speeds. Compare to exhaust turbine inlet temperature of SDE, LHRe has increased about 15 %, LHReth has decreased about 17 % at all engine speeds.
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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) | 0.002 | 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".