Performance Improvement of Mass Transfer Through Membrane Using Ultrasound for HVAC Application
Bibliographic record
Abstract
Abstract Liquid desiccant dehumidification is one of the energy-efficient alternatives to conventional air conditioning systems for humidity control. Membrane dehumidifier is preferred to avoid the desiccant carryover, which occurs in a conventional packed bed dehumidifier. However, its mass transfer performance is lesser than that of the packed bed dehumidifier. This is due to additional mass transfer resistance of the membrane between the air and desiccant. It is found that the resistance by the boundary layer formed at the membrane-air interface accounts for a significant portion of the overall mass transfer resistance. Breaking of such boundary layer using ultrasound is an attractive technique to reduce the resistance. The present study experimentally investigates the influence of ultrasound on the mass transfer performance of a membrane humidifier. Subsequently, with the experimental results of the humidifier, the effect of ultrasound on the performance of the membrane dehumidifier is numerically studied. The performances of humidifier and dehumidifier are presented in terms of moisture addition or removal rate and latent effectiveness. It is found that the vibration due to ultrasound enhances the performance of the membrane dehumidifier by 1.5 times.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".