Performance Definitions for Three-Fluid Heat and Moisture Exchangers
Bibliographic record
Abstract
This paper presents performance definitions for calculating the overall effectiveness of three-fluid heat and moisture exchangers. The three-fluid heat and moisture exchanger considered in this paper is a combination of a liquid-to-liquid heat exchanger for heat transfer between a desiccant solution and a refrigerant and an energy exchanger for heat and moisture transfer between desiccant solution and air streams. The performance definitions presented in this paper are used to calculate the overall sensible and latent effectivenesses of a three-fluid heat and moisture exchanger, which has been tested under air cooling and dehumidifying operating conditions in a previous work (Abdel-Salam et al., 2016, “Design and Testing of a Novel 3-Fluid Liquid-to-Air Membrane Energy Exchanger (3-Fluid LAMEE),” Int. J. Heat Mass Transfer, 92, pp. 312–329). The effectiveness of this three-fluid heat and moisture exchanger is compared when calculated using the traditional energy exchanger effectiveness equations and the overall performance definitions. Results show that the overall performance definitions provide effectiveness values that are less sensitive to changes in the inlet refrigerant temperature and therefore are more generally applicable for energy exchanger design than the traditional effectiveness equations used in the literature.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".