Characterization of the Combustion Process of Flame Resistant Thermal Protective Textiles in the Presence of Oily Contaminants: Effects of Contamination and Decontamination
Bibliographic record
Abstract
This paper reports two experimental studies wherein the combustion process of flame resistant (FR) thermal protective textiles is characterized in terms of thermal decomposition and heat release parameters before and after contamination and in terms of heat release parameters after contamination and decontamination. Aramid and FR cotton/nylon decomposed at higher and aramid/FR viscose at lower temperature in the presence of oil. Oil interferes with thermally induced interactions between aramid and FR viscose, altering the thermal decomposition rates and formation of char, and thereby increasing the effectiveness of the flame retardant present in the viscose. It is apparent that oily contaminants present in FR fabrics affect the initiation of the thermal degradation and formation of char. All contaminated FR fabrics showed significantly higher peak heat release rate (PHRR), total heat release (THR) and effective heat of combustion (EHC) compared to uncontaminated ones. Oily specimens laundered with no detergent or prewash product had higher PHRR, THR and EHC compared to other treatments regardless of the fabric type or number of contamination/decontamination cycles. Heat release increased with increased number of contamination/decontamination cycles for most laundry treatments for all FR fabrics. FR cotton/nylon had the highest and aramid had the lowest PHRR and THR whether specimens were uncontaminated, contaminated or decontaminated. In this study heat release from FR fabrics increased with increased oily contamination.
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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 | 0.000 |
| 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 | 0.000 | 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".