Numerical and experimental analysis of forced convection in rib‐roughened channels with moisture‐permeable walls
Bibliographic record
Abstract
Abstract Ribbed features can promote mixing and improve convective heat and mass transfer in channels. This can be beneficial in certain exchangers, such as Energy Recovery Ventilators (ERVs), which employ moisture‐permeable membranes to transfer both latent and sensible heat. In this work, a computational fluid dynamics model with experimental validation was used to study angled rib mixing features in compact channels. Results show that, relative to a smooth channel, the ribs increase the channel Sherwood and Nusselt numbers by a larger fraction than the corresponding increase in friction factor. For a typical commercial grade ERV, total effectiveness can be improved by over 10% for an equal pressure drop by adding ribs and slightly increasing the channel height. A custom test stand and rib‐forming technique were developed to validate the simulation predictions. The experiments confirm the net benefit of ribbed channels and agree with the simulation results within experimental uncertainty.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".