Using CFD Simulations to Improve the Air-Cooled Steam Condenser Performance in Severe Windy Conditions via Proper Tuning of Blades Pitch Angles
Bibliographic record
Abstract
The use of air-cooled steam condenser (ACSC) in thermal power plants has become so normal since a few decades ago. It is because there are so many valuable advantages with the ACSC implementation, e.g., little dependency on water consumption and benefiting from the forced convection heat transfer instead of the natural one to condense the steam. However, the thermal performance of an ACSC can be readily defected by the ambient wind; specifically, when the ambient temperature is high. This research work benefits from the computational fluid dynamics tool to study the details of ACSC’s thermal performance in such undesirable ambient windy conditions. Furthermore, this work suggests an effective remedy to increase the heat rate from the proposed ACSC. Evidently, the flow rate of cold air through the heat exchangers of proposed ACSC has direct influence in heat transfer rate from the heat exchangers of ACSC. One remedy to achieve higher cold air flow rates through these heat exchangers is to improve the design of its fans or blowers. However, for an ACSC already in service, one should look for other cost-effective remedies. So, if one wishes to improve the performance of those fans without changing their design one should pay attention to some other simple ways with little costs to implement them. This work suggests to tune up the pitch angles of blades of ACSC’s fans properly. The details of implementing this remedy are presented in this paper.
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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".