Feasibility Study on using the Heat Pipe Assembly to Enhance the Performance of Air-Cooled Condensers
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-1915.vid Power generation cycles, whether as a simple or combined cycle power plant, are facing with serious performance losses in summer times. In vapor-based thermodynamic cycles, the power production is mostly restricted by the poor performance of their condensers. The power plant indeed the air-cooled condensers are highly affected by environmental conditions. The impact is that there would be a sharp drop in thermal performance of an original air-cooled condenser. With the increase in ambient temperature, the poor performance of an air-cooled condenser leads to a serious decrease in turbine power production. The main goal of this research is to increase the performance of an air-cooled condenser using heat-pipes installed on proper locations at the air-cooled condenser. To achieve this, a numerical simulation is used to find the most suitable arrangement of the heat pipes, which are going to be installed in possible positions inside the condensate fluid tank of an air-cooled condenser. The main contribution of this work is that it, avoids two-phase flow simulation inside the heat pipe. The heat pipe is assumed as a solid metal with a very high thermal conductivity value. Next, the heat pipes are placed into the condensate tank of an air-cooled condenser at an ambient temperature of 35 °C using three different arrangements. Then, the entire system of ACC including the heat pipes are simulated suitably. Finally, the most appropriate arrangement is selected to provide the maximum amount of heat released from the original condenser. The simulation results indicate that the highest and lowest amount of heat release from the ACC are from 29.9 kW to 30.5 kW. The results show that the most suitable arrangement with the highest thermal performance occurs at ambient temperature of 35 °C.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".