Thermodynamic Modeling and Multi‐Objective Optimization of a New System Presented for Reutilization of the Lost Heat in Combined‐Cycle Power Plants
Bibliographic record
Abstract
In combined‐cycle power plants, a large amount of thermal energy is lost when the boiler and steam unit are out of order and the gas unit is operated in single mode. For the first time, this work suggests every combined‐cycle power plants should be equipped with this kind of energy system to recover the waste heat by producing hydrogen and generating electricity. This system combines a Rankine cycle with a thermoelectric generator, a finned‐tube heat exchanger, and a proton exchange membrane to produce hydrogen. Having been designed, the suggested energy system is assessed by energy, exergy, and exergo‐economy laws. Furthermore, the impacts of some effective factors on the efficiency and the costs are precisely analyzed. Eventually, the presented system is optimized considering two main purposes of exergy efficiency and costs. The achieved results show that the proposed system can effectively link to the gas unit to restore and even save the lost thermal energy in the single‐mode condition. The conducted optimization attenuates the objective parameter of exergy efficiency from 48.39% to 41.65% and diminishes the costs from 550.14 to 480.82 $ GJ−1. Eventually, the optimization causes to rise from 1.2 to 1.32 kg h−1.
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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 | 0.001 |
| 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".