Exergy Analysis of Heat Recovery Steam Generator: Effects of Supplementary Firing and Desuperheater
Bibliographic record
Abstract
Abstract Comprehensive exergy analysis of a heat recovery steam generator (HRSG) with two levels of delivered pressure is presented. The effects of supplementary firing as well as desuperheater set-point are considered to evaluate the exergy destruction of HRSG components. Burner firing rate is limited to a value that corresponds to the maximum allowable temperature of tube metal of high-pressure (HP) superheater. According to the exergy analysis performed in the current study, the exergy efficiency of HRSG is about 80% which means 20% of flue gas exergy (entering HRSG) is dissipated by HRSG destruction (∼14%) and stack exergy loss (∼6%). The stack exergy loss drops continuously as supplementary firing raises. It has also been determined that increasing the rate of supplementary firing boosts the exergy efficiency in the absence of water spray and reduces it when desuperheater is working. In addition, the exergy delivered to steam turbine shows a linear growth with burner heat while it is hardly affected by the set-point of desuperheater. Also, it is found that exergy loss through the stack is not sensitive to desuperheater set-point while it is on the decrease as burner duty raises. HP steam flow will raise with increasing the firing and/or decreasing the desuperheater set-point. HP evaporator has the most contribution in exergy destruction among HRSG components (∼40%), whereas HP superheater and desuperheater are components with a maximum sensitivity of exergy destruction to the amount of water spray.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".