Evidence map›Paper›PMID 29483557›Full record

ArticleScientific reports2018

Development of a numerical model to predict physiological strain of firefighter in fire hazard.

Yun Su, Jie Yang, Guowen Song, Rui Li, Chunhui Xiang, Jun Li

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 10 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Yun SuCollege of Fashion and Design, Donghua University, Shanghai, 200051, China.
Jie YangIowa State University, Ames, 50010, Iowa, USA.
Guowen SongIowa State University, Ames, 50010, Iowa, USA. gwsong@iastate.edu.
Rui LiIowa State University, Ames, 50010, Iowa, USA.
Chunhui XiangIowa State University, Ames, 50010, Iowa, USA.ORCID 0000-0002-8570-1863
Jun LiCollege of Fashion and Design, Donghua University, Shanghai, 200051, China.
Iowa State University · USDonghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper aims to develop a numerical model to predict heat stress of firefighter under low-level thermal radiation. The model integrated a modified multi-layer clothing model with a human thermoregulation model. We took the coupled radiative and conductive heat transfer in the clothing, the size-dependent heat transfer in the air gaps, and the controlling active and controlled passive thermal regulation in human body into consideration. The predicted core temperature and mean skin temperature from the model showed a good agreement with the experimental results. Parametric study was conducted and the result demonstrated that the radiative intensity had a significant influence on the physiological heat strain. The existence of air gap showed positive effect on the physiological heat strain when air gap size is small. However, when the size of air gap exceeds 6 mm, a different trend was observed due to the occurrence of natural convection. Additionally, the time length for the existence of the physiological heat strain was greater than the existence of the skin burn under various heat exposures. The findings obtained in this study provide a better understanding of the physiological strain of firefighter and shed light on textile material engineering for achieving higher protective performance.

Indexed as

FirefightersFiresBody Temperature RegulationHeat-Shock ResponseHeat Stress DisordersHumansModels, TheoreticalTextilesThermal Conductivity

Identifiers

PMID29483557
PMCPMC5827774
OpenAlexW2792833826

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.