Quantifying errors in coupled ε-NTU method and development of divisional ε-NTU method for reliable and accurate design of energy exchangers
Bibliographic record
Abstract
In coupled energy exchangers, where heat and mass transfer rates are interdependent due to the phase change energy associated with moisture transfer, the classical ϵ -NTU method can lead to significant errors in estimating performance. The coupled ϵ -NTU method can be used to mitigate these errors and uses modified non-dimensional parameters called the effective heat and mass capacity ratios. While more accurate than the classical ϵ -NTU method, it still has significant errors in estimating performance under certain operating conditions. The coupled ϵ -NTU method is compared to a numerical model to evaluate the performance of a liquid-to-air membrane energy exchanger (LAMEE). The operating conditions for which the coupled ϵ -NTU method is reliable are identified to help designers make informed choices. It was also found that the errors in estimating the total energy transfer are within 5 % when Cr* (specific heat capacity ratio of solution-to-air) > 4; however, when Cr* is less than 1, the errors in the coupled ϵ -NTU method are high. To overcome the limitations of the coupled method, the divisional ϵ -NTU method is proposed. It relies solely on algebraic equations and accurately predicts sensible and latent heat transfer with an error of less than 5 % under all operating conditions compared.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".