Dynamic exergetic performance assessment of an integrated solar pond
Bibliographic record
Abstract
In this paper, we present an experimental investigation of the exergetic performance of a solar pond integrated with solar collectors (with a surface area of 2096 m² and a depth of 2 m, and four flat–plate collectors with dimensions of 1.90 m × 0.90 m). A data acquisition device is used to measure and record the temperatures hourly at various locations in the pond. An exergy model is developed to study the dynamic exergetic performance of the solar pond integrated with solar collectors in terms of exergy efficiencies which are then compared with the corresponding energy efficiencies. Thus, the energy efficiencies are found to be 21.33%, 23.59%, 24.28% and 26.52%; the exergy efficiencies are found to be 20.02%, 21.66%, 22.24% and 23.84% for using 1, 2, 3 and 4 collectors, respectively. The energy efficiencies are compared with the corresponding exergy efficiencies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".