State-of-the-art in solar water heating (SWH) systems for sustainable solar energy utilization: A comprehensive review
Bibliographic record
Abstract
The solar water-heating (SWH) system is one of the most convenient applications of solar energy, which is considered an available, economical, and environmentally friendly energy source to fulfill the energy demands of the world. In this review, existing SWH systems and design aspects of major components e.g., solar thermal collector, storage tank, heat exchanger, heat transferring fluid, absorber plate, etc. were extensively studied. Recent research to further improve SWH systems and potential practical applications are critically reviewed. Moreover, a relatively new concept in SWH systems, which is using nanofluids in solar collectors as heat transfer fluid has been studied in terms of design criteria for the development of SWH systems. Stationary flat plate collector (FPC) and single-axis tracking compound parabolic collector (CPC) exhibit thermal efficiencies of 45–60 % (operating range: 25–100 °C) and 30–50 % (operating range: 60–300 °C), respectively. The use of thermal stratification structures e.g., diffusers, baffles, membranes, fabrics, etc. is an effective tool to reduce heat losses from the storage tank as well as to harvest the highest energy from the solar collector. Coating of nanomaterials e.g., nickel, copper, etc. was found to reduce the backside heat loss in SWJ systems which eventually increases the thermal performance of the system. Nanofluids consisting of multiwall carbon nanotubes (MWCNTs) and Al2O3 increased the effectiveness of FPC by 28.3 and 35 %, respectively. Moreover, using CuO nanofluids, the collector efficiency of a typical evacuated tube collector (ETC) was increased by up to 12.4 %. Several potential future recommendations for improving the performance of the SWH system were stated.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".