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Record W1154958140 · doi:10.1520/stp104097

Non-destructive Test Methods to Assess the Level of Damage to Firefighters' Protective Clothing

2012· book-chapter· en· W1154958140 on OpenAlexaff
Moein Rezazadeh, David A. Torvi

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsClothingTest (biology)Forensic engineeringEngineeringGeographyBiology

Abstract

fetched live from OpenAlex

During the service life of firefighters' protective clothing, individual aspects of its performance change due to factors such as thermal exposure. Although there are some standards for the inspection of firefighters' protective clothing, test methods that could be used to completely determine the level of damage and the remaining service life of such clothing have not yet been developed. In order to develop these test methods, it is necessary to understand how individual aspects of the performance of protective clothing deteriorate after exposure to fireground conditions. In this project, specimens consisting of an outer shell, a moisture barrier, and a thermal liner were thermally aged and tested using 20 kW/m2 exposures in a cone calorimeter. Two different outer shell fabrics, one undyed (light brown in color) and one dyed (black), were tested. Changes in the tensile strength of the outer shell resulting from single and multiple exposures were measured. Changes in the color of the outer shell were also measured using digital image analysis. The study demonstrates that multiple exposures to this heat flux level were less destructive than a single exposure of the same total duration. Color measurements showed good potential as a possible nondestructive means of evaluating the condition of the outer shell fabric, as these color measurements could be correlated to the loss in tensile strength of the outer shell. Possible future work to evaluate other aspects of the performance of these materials is discussed.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.207
GPT teacher head0.394
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreOther

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".

Quick stats

Citations4
Published2012
Admission routes1
Has abstractyes

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