The effect of air gaps in moist protective clothing on protection from heat and flame
Bibliographic record
Abstract
The distribution of air gaps and moisture in thermal protective clothing has a large and complicated impact on thermal protective performance. The effect of air gap size on the thermal protective performance of flame-resistant fabrics with different moisture content was investigated under intense exposures. The air gap sizes from 0 to 24 mm were analyzed using an air gap height regulation device. Fabrics with different moisture content were prepared, and the thermal protective performance was evaluated. The results showed that the effect of air gaps was influenced by the amount of moisture added to the fabric. It was also determined that the moisture in the fabric significantly increased the thermal protective performance ( P < 0.05). The positive effect of moisture was enhanced by the amount of moisture if the air gap size was less than 12 mm; the effect of moisture varied for air gaps larger than 12 mm. The mechanisms associated with heat and mass transfer in moist fabric were discussed. The results suggest that protective clothing design should consider the combined effects of air gap and moisture. Based on the current study, air gaps of 9–12 mm seem to achieve maximum thermal protection.
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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 | 0.000 | 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) | 0.001 | 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".