MétaCan
Menu
Back to cohort

Investigation of the frost limits of a liquid-to-air membrane energy exchanger (LAMEE) under subzero air temperatures

2025· article· en· W4413327954 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Heat and Mass Transfer · 2025
Typearticle
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFrost (temperature)Materials scienceHeat exchangerLiquid airEnvironmental scienceMechanicsThermodynamicsNuclear engineeringComposite materialChemistryPhysics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.277
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it