Heat and moisture transfer through skin-clothing microclimate
Why this work is in the frame
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Bibliographic record
Abstract
• Heat and moisture transfer between skin, microclimate, porous fabric, and the ambient was experimentally and numerically studied. • Vapor concentration, temperature, and airflow in microclimate were analyzed. • Heat and moisture transfer changes with microclimate thickness, tilt angle, and ambient airflow. • Nusselt and Sherwood numbers were evaluated and related to transfer modes. The microclimate between clothing and human skin plays an important role in the heat and moisture exchange between body and ambient environment, which is essential to the thermo-physiological comfort. Despite extensive research on microclimate heat transfer, the sweating process accompanying heat transfer has often been neglected, and the investigation of transport mechanisms is limited. In this study, the heat and moisture transfer from skin to environment was experimentally and numerically simulated with focus on factors such as microclimate thickness (0 mm ∼ 40 mm), tilt angle (0° ∼ 90°), and airflow direction (parallel and normal to the fabric surface). The skin was represented by a surface with uniform temperature in experiments and numerical simulations, and the fabric was modeled as an air-permeable porous medium in the numerical simulations. The experimentally validated numerical model provided detailed distributions of temperature, vapor concentration, and airflow patterns in the microclimate for both dry and wet skins. The airflow of natural convection featured multiple circulation cells, and their circulation times were calculated and then related to the microclimate transport performance. It was found that natural convection dominates the heat and moisture transfer in thicker microclimates. It was also found that normal airflow was more effective in facilitating the heat and moisture transfer as compared to parallel airflow. The results are useful for developing high-performance clothing optimized for thermal regulation and moisture management, improving comfort and safety in different conditions.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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 it