| Title: | CFD-based analysis of deviations between thermocouple measurements and local gas temperatures during the cooling phase of compartment fires |
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| Authors: | ID Put, Florian (Author)
ID Lucherini, Andrea (Author)
ID Van Coile, Ruben (Author)
ID Merci, Bart (Author) |
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| Files: |  URL - Source URL, visit https://www.sciencedirect.com/science/article/pii/S0379711224001899
 PDF - Presentation file. (1,43 MB, This file will be accessible after 17.10.2026)
MD5: 5F5DE34EF076EDB96E1328327B392A8D
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| Language: | English |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: |  ZAG - Slovenian National Building and Civil Engineering Institute
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| Abstract: | Data from thermocouple (TC) measurements play a pivotal role in fire safety science and engineering studies. It is well-known that there are deviations from the actual local gas temperature and many studies have led to the development of correction factors. The present study focuses on these deviations inside compartments through a systematic series of CFD simulations, performed with Fire Dynamics Simulator (FDS), version 6.8.0. A canonical cubic box is used as geometry. This allows for the demonstration of the impact of the presence of smoke, with variable optical thickness, on the TC data as retrieved from FDS. Significant differences are observed between TC measurements and local gas temperatures. Corrections as developed for TC measurements in open atmospheres cannot be readily applied in compartment configurations, where smoke properties change both spatially and temporally. |
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| Keywords: | thermocouple measurements, CFD simulations, heat transfer, compartment fires, cooling, fire dynamics, FDS |
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| Publication status: | Published |
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| Publication version: | Author Accepted Manuscript |
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| Publication date: | 17.10.2024 |
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| Publisher: | Elsevier |
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| Year of publishing: | 2024 |
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| Number of pages: | str. 1-14 |
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| Numbering: | vol. 150, part B, [article no.] 104276 |
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| UDC: | 62 |
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| ISSN on article: | 1873-7226 |
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| DOI: | 10.1016/j.firesaf.2024.104276  |
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| COBISS.SI-ID: | 212307203 |
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| Copyright: | © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. |
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| Publication date in DiRROS: | 28.10.2024 |
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| Views: | 7 |
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| Downloads: | 2 |
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