Characterizing thermal protective fabrics of firefighters’ clothing in hot surface contact
Why this work is in the frame
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Bibliographic record
Abstract
This study characterizes the thermal protective fabrics of firefighters’ clothing under the exposure of hot surface contact. For this, thermal protective performance of different fabrics was evaluated using a laboratory-simulated hot surface contact test, and various factors affecting the performance were statistically identified. Additionally, heat transfer mechanisms during testing were analytically and mathematically modeled. It has been found that fabric’s constructional features and properties are the key factors to affect its thermal protective performance. In this study, the presence of a thicker thermal liner in a layered fabric system resulted in higher performance; in contrast, a multi-layered fabric system incorporating a moisture barrier in its outer layer displayed the lowest performance. Furthermore, it was demonstrated that a fabric’s air permeability has a minimal impact on performance, whereas weight, thickness, and thermal resistance have a significant positive impact on performance. Based on the analytical and mathematical models developed, it was apparent that conductive heat transfer mainly occurs through fabric during testing, and this conductive heat transfer depends upon the surface roughness and thermal properties (thermal conductivity, density, and specific heat) of the tested fabric. Here, thermal contact resistance between the hot surface and fabric also plays a crucial role in the heat transfer or thermal protective performance of fabric. Moreover, the heat transfer gradually decreases across fabric thickness, which can substantially affect thermal protective performance. This study can advance the theory of textile/materials science through better understanding of heat transfer in fabrics. This understanding can help in developing an integrated knowledge of fabric properties, heat transfer through fabrics, and thermal protective performance of fabrics. The findings from this study can also assist textile/material engineers with the development of a high performance thermal protective fabric for clothing to provide better occupational safety and health for firefighters.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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