Transient Analysis of a Flat-Plate Direct Absorption Solar Collector with Nanofluids
Bibliographic record
Abstract
The thermal performance of a direct absorption solar collector (DASC) can be improved by enhancing the absorbing plate or the effectiveness of the heat transfer fluid. This can be achieved by using a nanofluid instead of pure water, as it possesses better optical properties. This paper conducts numerical simulations on a two-dimensional transient forced convection inside a DASC with a horizontal channel to predict its transient thermal behavior in a specific geographical location under varying hourly solar radiation. The working fluid used is a nanofluid comprised of water and carbon nanohorn nanoparticles, with concentrations ranging from 0 (pure water) to 0.05 g/L. Additionally, the inlet mass flow rate has five varying values from 0.001 to 0.2 kg/s. Results detailing temperature and system efficiency are presented, with their evolution throughout the day also reported. The analysis indicates that the system's performance improves with increasing concentration for each inlet mass flow rate value. Conversely, keeping the concentration constant, the temperature rises as the inlet mass flow rate decreases.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".