Numerical studies on thermo-hydraulic performance of solar air heater with quarter circle roughness ribs
Bibliographic record
Abstract
With their diverse range of applications, solar air heaters transform renewable solar energy into useful heat. The efficiency of solar air heater can be enhanced by exploring the effects of novel rib configurations. Despite the extensive work done so far on roughened solar air heaters, insufficient attention has been paid to the unique geometric features and potential advantages of quarter-circle ribs with respect to improving heat transfer efficiency. The fluid flow and heat transfer properties of a roughened solar air heater with quarter-circle-shaped ribs were examined in-depth using numerical analysis to improve the efficiency. The k-ε RNG turbulence model was used to conduct 2D steady-state numerical simulations, and the findings showed excellent agreement with the smooth duct and related literatures. The impact of rib spacing was explored by changing the rib relative pitch (p/e) from 6.67 to 13.3 for Reynolds range of 4000-20,000. The thermo-hydraulic performance factor was found to be 1.63. Additionally, it was shown that an increase in relative pitch (p/e) of 6.67 to 10 resulted in an increase in the Nusselt number for all Re values examined. At Re of 16,000, an enhancement of 2.42 times the Nu was made for p/e = 6.67. It was also noted that for all Re values taken into consideration, Nu falls with an increase in p/e from 10 to 13.3.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".