Exergoenvironmental evaluation of kalina power generation system
Bibliographic record
Abstract
The basic needs of man are food, clothing, and shelter besides air and water. In providing these needs, power generation systems play a crucial role. Day by day, for various reasons such as explosion of population, the demand for power is increasing tremendously. Power generation systems need to generate more power. A novel power generation system suitable for recovering waste heat at a medium temperature range is examined in the present work. To assess the performance of a power generation system, energy and exergy measures are necessary. Energy measures provide enough details about the performance of the system. To know the systematic performance analysis, detailed exergy analysis alternatively profound as advanced exergy analysis and environmental impact are to be investigated. Exergoenvironmental analysis on the proposed Kalina power generation system has been carried out under hot sink conditions. Considering the proposed decision variables relative exergy destruction (ĖD/ĖP), relative environmental impact (Ẏ/ĖP), and relative investment cost (Ż/ĖP), the performance of the system has been assessed. The exergy destruction and the destruction cost rate of 29.23 kW and 0.478 $/hr at turbine inlet conditions of 185°C and 45 bar have been achieved. The exergoenvironmental factor fb and the relative difference rb have revealed that the components with high environmental impact have to be minimized. Turbine and HE4 are the components that contribute to higher total exergy and devise related impact on the environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".