Performance Analysis of an Irreversible Regenerative Brayton Cycle Based on Ecological Optimization Criterion
Bibliographic record
Abstract
An ecological optimization along with a detailed parametric analysis of an irreversible regenerative Brayton cycle with finite heat capacity of external reservoirs have been carried out. The external irreversibilities due to finite temperature difference and internal irreversibilities due to fluid friction losses in compressor / turbine, regenerative heat loss, pressure loss are included in the analysis. Ecological function is thermodynamically optimized which is defined as the power output minus the product of environment temperature and entropy generation rate. A detailed analysis shows that the ecological function and corresponding power output / thermal efficiency can be maximized with judicious selection of parameters such as efficiency of turbine and compressor, effectiveness of various heat exchangers, heat source inlet temperature, pressure drop recovery coefficients and heat capacitance rate of the working fluid. It is found that the regenerative effectiveness is more prominent for maximum ecological function and corresponding thermal efficiency while cold side effectiveness is dominant factor for corresponding power output. It is also found that the effect of turbine efficiency (ηt) is more than the compressor efficiency (ηc) on the thermodynamic performance of an irreversible regenerative Brayton heat engine cycle. The model analyzed in this paper gives lower values of various performance parameters as expected and replicates the results of an irreversible regenerative Brayton cycle model discussed in the literature at pressure recovery coefficients of α1=α2=1.
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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".