Performance investigation of liquid-to-air membrane energy exchanger under low solution/air heat capacity rates ratio conditions
Bibliographic record
Abstract
Liquid-to-air membrane energy exchanger is a novel membrane base energy exchanger, which allows both heat and moisture transfer between air and a salt solution. The heat and mass transfer performance of a single one is significantly dependent on two dimensionless parameters: number of heat transfer units and the ratio of heat capacity rates between solution flow and air flow (Cr*). The performance of liquid-to-air membrane energy exchanger under high Cr* (i.e. Cr* ≥ 1) has been comprehensively investigated experimentally and numerically in previous research. In this study, the effectiveness of a small-scale liquid-to-air membrane energy exchanger under low Cr* conditions (i.e. Cr* < 1) is experimentally tested. Good agreement between the experimental and numerical results is achieved under low Cr* cases. Practical application: The ideal energy exchanger is one that can transfer both heat and moisture because during hot and humid conditions such an exchanger is capable of transferring up to four times as much energy as an exchanger that can transfer sensible heat only. It is beneficial if the exchanger can transfer heat and moisture also between remote supply and exhaust airstreams, as this may minimize the ducting required and reduces contaminant transfer from one airstream to the other. This is very important for applications such as hospitals, laboratories, and manufacturing facilities, where slight cross contamination can cause serious health effects.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".