Thermal Effusivity Assessment of Sportswear Fabrics in the Dry State: Stacked and Air-Hoop Methods
Bibliographic record
Abstract
ABSTRACT In recent years, thermal effusivity, a property that describes the warm or cool touch perception, has gained significant attention in the apparel industry as it contributes to human thermophysiological comfort. The current study aims to explore the thermal effusivity of 27 sportswear fabrics, including woven and knitted structures with various fiber contents, using the stacked method (according to ASTM D7984-21, Standard Test Method for Measurement of Thermal Effusivity of Fabrics Using a Modified Transient Plane Source (MTPS) Instrument) and a modified air-hoop method. The results obtained revealed that the pressure range specified in ASTM D7984-21 (10–50 kPa) may cause fabric compression, resulting in the measurement of a material-based thermal effusivity rather than the fabric thermal effusivity. A pressure of 1 kPa was found to be more appropriate for obtaining accurate measurements of sportswear fabrics without altering their three-dimensional structure. Furthermore, a strong correlation was observed between the stacked and air-hoop methods for fabrics with thicknesses close to or greater than 0.4 mm. The air-hoop method simulates the configuration when the fabric is worn as part of a garment. The new knowledge provided by this research will enhance the accuracy of the thermal effusivity measurement of sportswear fabrics. It will contribute to the development of more comfortable fabrics considering realistic garment use scenarios.
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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 | 0.001 | 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) | 0.001 | 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".