Exergy analysis of high-performance cycles for gas turbine with air-bottoming
Bibliographic record
Abstract
Exergy is described as a measure for identifying and explaining the benefits of technologies. Therefore in this research the performance of water and steam injection in the gas turbine with air bottoming cycle (ABC) is evaluated based on an exergy analysis and thermodynamic laws. In this study, we suggest four efficient cycles incorporated to theABC that three of them are novel. The cycles are: water injection-1 (WI-ABC-1), water injection-2 (WI-ABC-2), steam injection-1 (SI-ABC-1) and steam injection-2 (SI-ABC-2). The analysis results show the cycles have more thermal efficiency, net output power and exergy recovery respectively. The SI-ABC-1 and SI-ABC-2 were found to have minimum exergy loss and maximum output power in the same operating conditions. The lowerexergy loss is caused due to more heat recovery in the regenerator in the SI-ABC cycles, and more inlet mass to bottoming turbine results in a higher output power. Also, this research investigates the effects variations of pressure ratio, ambient temperature and turbine inlet temperature on outputs. Key words: Air bottoming cycle (ABC) gas turbine, water injection, steam injection, exergy analysis, exergy recovery.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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".