Issue |
MATEC Web Conf.
Volume 290, 2019
9th International Conference on Manufacturing Science and Education – MSE 2019 “Trends in New Industrial Revolution”
|
|
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Article Number | 12025 | |
Number of page(s) | 15 | |
Section | Safety and Health at Work | |
DOI | https://doi.org/10.1051/matecconf/201929012025 | |
Published online | 21 August 2019 |
Importance of Experimental Tests for the Determination of Modeling Parameters in Fire Safety Engineering
1 Department of Theoretical and Applied Sciences, Insubria University, Via Vico, 46 – 21100, Varese, Italy
2 Department of Sciences and High Technology, Insubria University, Via Vico, 46 – 21100, Varese, Italy
3 Department of Civil, Building and Environmental Engineering (DICEA), Sapienza University of Rome, Via Eudossiana 18 - 00184, Rome, Italy
4 Department of Civil Environmental and Mechanical Engineering, University of Trento, via Mesiano 77, 38123, Trento, Italy
In the field of Fire Safety Engineering, the application of mathematical models is crucial in order to properly estimate the severity of eventual fires occurring inside workplaces. Such models (like CFast, Ozone, FDS, CFX, Fluent), require a notable amount of specific parameters in order to work. Such parameters are usually available in the current literature, or they can be estimated via experimental tests. In this work, several experimental setups have been performed in order to evaluate such data in the burning of a wide range of materials: cotton, polyethylene and polyester in industrial rollers, flour, sugar, feed for dairy cows, and wood pallets. Cone Calorimeter, Mahler bomb, and real-scale tests have been performed in order to evaluate parameters such as Calorific Values, Total Heat Released, Heat Released Rate and smoke composition analysis. The real-scale tests have been performed with the aim of addressing fire occurring in warehouses, focusing then on an industrial environment. All the values have been compared with theoretical estimations made with the ClaRaf 2.0 software, and it was noticed that they tend to give overestimated values in comparison with empirical results.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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