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Open AccessReview

A Review of Modelling and Simulation Methods for Flashover Prediction in Confined Space Fires

1
Department of Computer Technology, Universidad de Alicante, 03690 Alicante, Spain
2
ELIS Department, Research group IDLab, Ghent University—IMEC, 9052 Ghent, Belgium
*
Author to whom correspondence should be addressed.
Current address: Department of Computer Technology, Universidad de Alicante, ap. de correos 99, 03080 Alicante, Spain.
Current address: ELIS Department, Research Group IDLab, Technologiepark-Zwijnaarde 19, B-9052 Ghent, Belgium.
Appl. Sci. 2020, 10(16), 5609; https://doi.org/10.3390/app10165609
Received: 6 July 2020 / Revised: 6 August 2020 / Accepted: 11 August 2020 / Published: 13 August 2020
(This article belongs to the Special Issue Computing and Artificial Intelligence for Visual Data Analysis)
Confined space fires are common emergencies in our society. Enclosure size, ventilation, or type and quantity of fuel involved are factors that determine the fire evolution in these situations. In some cases, favourable conditions may give rise to a flashover phenomenon. However, the difficulty of handling this complicated emergency through fire services can have fatal consequences for their staff. Therefore, there is a huge demand for new methods and technologies to tackle this life-threatening emergency. Modelling and simulation techniques have been adopted to conduct research due to the complexity of obtaining a real cases database related to this phenomenon. In this paper, a review of the literature related to the modelling and simulation of enclosure fires with respect to the flashover phenomenon is carried out. Furthermore, the related literature for comparing images from thermal cameras with computed images is reviewed. Finally, the suitability of artificial intelligence (AI) techniques for flashover prediction in enclosed spaces is also surveyed. View Full-Text
Keywords: flashover; artificial intelligence; CFD software; prediction; thermal vision camera; thermal image flashover; artificial intelligence; CFD software; prediction; thermal vision camera; thermal image
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MDPI and ACS Style

Cortés, D.; Gil, D.; Azorín, J.; Vandecasteele, F.; Verstockt, S. A Review of Modelling and Simulation Methods for Flashover Prediction in Confined Space Fires. Appl. Sci. 2020, 10, 5609.

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