Effects of moisture content and clothing fit on clothing apparent ‘wet’ thermal insulation: A thermal manikin study
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.
Bibliographic record
Abstract
‘Wet’ thermal insulation, defined as the thermal insulation when clothing gets partially or fully wet, is an important physical parameter to quantify clothing thermal comfort. As the water/sweat gradually occupies the intra-yarn and inter-yarn air voids of the clothing material, the clothing intrinsic thermal insulation will be diminished and, hence, contribute to the loss of total insulation. In cold conditions, a loss in total thermal insulation caused by sweating may result in an inadequate thermal insulation to keep thermal balance and eventually leads to the development of hypothermia and cold injuries. Therefore, it is imperative to investigate the effect of clothing fit and moisture content on clothing ‘wet’ insulation. In this study, the ‘wet’ thermal insulation of three two-layer clothing ensembles was determined using a Newton thermal manikin. Four levels of moisture content were added to the underwear: 100, 200, 500 and 700 g. The clothing apparent ‘wet’ thermal insulation under different testing scenarios was calculated and compared. A third-degree polynomial relationship between the reduction in ‘wet’ thermal insulation and the moisture content added to underwear was obtained. Further, it was evident that the clothing fit has a minimal effect on the apparent ‘wet’ thermal insulation. The findings may have important applications in designing and engineering functional cold weather clothing and immersion suits.
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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 | 0.007 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it