Investigation of the frost limits of a liquid-to-air membrane energy exchanger (LAMEE) under subzero air temperatures
Bibliographic record
Abstract
Liquid-to-air membrane energy exchangers (LAMEEs) are resistant to frosting due to moisture transfer through the membrane. Systems that work under freezing temperatures can benefit from frost prevention through integration with LAMEEs. While some studies have investigated frost formation in LAMEEs, frost limits under subzero air temperatures have not been studied before. This paper aims to address the knowledge gap by investigating the frost limits of a LAMEE under air temperatures ranging from 0 to ‑30°C. At each air temperature, frost limits are identified experimentally over a wide range of air relative humidity. In addition, an analytical frost prediction model is used to predict the frost limits, and the results are compared with the experimental results. The results indicate that the LAMEE can effectively suppress frosting at air temperatures ranging from 0 to ‑30°C, though the frost prevention potential diminishes as the air temperature decreases. The findings can inform the design of future frost-free systems that work in cold air temperatures, such as frost-free cold-climate heat pumps.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".