Reviewing the Exergy Analysis of Solar Thermal Systems Integrated with Phase Change Materials
Bibliographic record
Abstract
The application of thermal storage materials in solar systems involves materials that utilize sensible heat energy, thermo-chemical reactions or phase change materials, such as hydrated salts, fatty acids paraffin and non-paraffin like glycerol. This article reviews the various exergy approaches that were applied for several solar systems including hybrid solar water heating, solar still, solar space heating, solar dryers/heaters and solar cooking systems. In fact, exergy balance was applied for the different components of the studied system with a particular attention given to the determination of the exergy efficiency and the calculation of the exergy during charging and discharging periods. The influence of the system configuration and heat transfer fluid was also emphasized. This review shows that not always the second law of thermodynamics was applied appropriately during modeling, such as how to consider heat charging and discharging periods of the tested phase change material. Accordingly, the possibility of providing with inappropriate or not complete results, was pointed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".