Supercharging of Diesel Engine with Compressed Air: Experimental Investigation on Greenhouse Gases and Performance for a Hybrid Wind-Diesel System
Bibliographic record
Abstract
Supercharging is the process of supplying air for combustion at a pressure greater than that achieved by natural or atmospheric induction, as applied to internal combustion engines. As a consequence of demonstrated technological, economical and energetic advantages in multiple literature evaluations concerning the large scale wind-compressed air hybrid storage system with gas turbines, the utilization of a hybrid wind-diesel system with compressed air storage (HWDCAS) has been frequently explored. These will mainly have average or small scale application such as the powering of isolated sites. It has been proven in numerous studies that the HWDCAS combined with an additional supercharging of the diesel engines will contribute to the increase of the power and efficiency of the diesel engine, the reduction of both fuel consumption and the emission of greenhouse gases (GHG). This article presents the obtained results from experimental validation of the selected design with an aim to valorize this innovative solution and become trustworthy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".