Numerical Prediction of Cables Fire Behaviour Using Non-Metallic Components in Cone Calorimeter

References

• Alonso, A., D. Lázaro, M. Lázaro, and D. Alvear. 2022. Self-heating evaluation on thermal analysis of polymethyl methacrylate (PMMA) and linear low-density polyethylene (LLDPE). 147 (18):10067–81. J Therm Anal Calorim. doi:10.1007/s10973-022-11364-x.
   Google Scholar
• Alonso, A., M. Lázaro, P. Lázaro, D. Lázaro, and D. Alvear. 2019. LLDPE kinetic properties estimation combining thermogravimetry and differential scanning calorimetry as optimization targets. J Therm Anal Calorim 138 (4):2703–13. doi:10.1007/s10973.
   Web of Science ®Google Scholar
• Astm, E. 2013. Standard test methods for measurement of synthetic polymer material flammability using a Fire Propagation Apparatus (FPA). Annu. Book Stand. doi:10.1520/E2058-13.
   Google Scholar
• Bal, N., and G. Rein. 2015. On the effect of inverse modelling and compensation effects in computational pyrolysis for fire scenarios. Fire Saf. J. 72:68–76. doi:10.1016/j.firesaf.2015.02.012.
   Web of Science ®Google Scholar
• Beji, T., and B. Merci. 2018. Numerical simulations of a full‐scale cable tray fire using small‐scale test data. Fire Mater 43 (5):486–96. doi:10.1002/fam.2687.
   Web of Science ®Google Scholar
• Duan, Q. Y., V. K. Gupta, and S. Sorooshian. 1993. Shuffled complex evolution approach for effective and efficient global minimization. J Optimiz Theory App 76 (3):501–21. doi:10.1007/bf00939380.
   Web of Science ®Google Scholar
• Gallo, E., W. Stöcklein, P. Klack, and B. Schartel. 2016. Assessing the reaction to fire of cables by a new bench‐scale method. Fire Mater 41 (6):768–78. doi:10.1002/fam.2417.
   Web of Science ®Google Scholar
• Ghorbani, Z., R. Webster, M. Lázaro, and A. Trouvé. 2013. Limitations in the predictive capability of pyrolysis models based on a calibrated semi-empirical approach. Fire Saf. J. 61:274–88. doi:10.1016/j.firesaf.2013.09.007.
   Web of Science ®Google Scholar
• Girardin, B., G. Fontaine, S. Duquesne, and S. Bourbigot. 2016. Fire tests at reduced scale as powerful tool to fasten the development of flame-retarded material: Application to cables. J Fire Sci 34 (3):240–64. doi:10.1177/0734904116642618.
   Web of Science ®Google Scholar
• Girardin, B., G. Fontaine, S. Duquesne, M. Försth, and S. Bourbigot. 2015. Characterization of thermo-physical properties of EVA/ATH: Application to gasification experiments and pyrolysis modeling. Materials 8 (11):7837–63. doi:10.3390/ma8115428.
   PubMed Web of Science ®Google Scholar
• Grayson, S., P. Van Hees, U. Vercellotti, H. Breulet, and A. Green. 2000. Fire performance of electrical cables – new test methods and measurement techniques. Final report of European Commission. SMT Programme Sponsored Research Project SMT4-CT96-2059. SMT Programme Sponsored Research Project SMT4-CT96-2059. Interscience Communications London 410. ISBN 0-9532312-5-9.
   Google Scholar
• Hehnen, T., L. Arnold, and S. La Mendola. 2020. Numerical fire spread simulation based on material Pyrolysis—An application to the CHRISTIFIRE phase 1 horizontal cable tray tests. Fire 3 (3):33. doi:10.3390/fire3030033.
   Google Scholar
• Hehnen, T., L. Arnold, P. Van Hees, and S. La Mendola 2018. Simulation of fire propagation in cable tray installations for particle accelerator facility tunnels. Proc 8th International Symposium on Tunnel Safety and Security ISTSS March 14-16, 2018. Borås (Sweden).
   Google Scholar
• Hopkins, D., and J. G. Quintiere. 1996. Material fire properties and predictions for thermoplastics. Fire Saf. J. 26 (3):241–68. doi:10.1016/S0379-7112(96)00033-1.
   Web of Science ®Google Scholar
• ISO. 2015. Reaction-to-fire tests — heat release, smoke production and mass loss rate — part 1: Heat release rate (cone calorimeter method) and smoke production rate (dynamic measurement).
   Google Scholar
• Kempel, F., B. Schartel, G. T. Linteris, S. I. Stoliarov, R. E. Lyon, R. N. Walters, and A. Hofmann. 2012. Prediction of the mass loss rate of polymer materials: Impact of residue formation. Combust. Flame 159 (9):2974–84. doi:10.1016/j.combustflame.2012.03.012.
   Web of Science ®Google Scholar
• Lautenberger, C., and C. Fernandez-Pello. 2011. Optimization algorithms for material pyrolysis property estimation. Fire Saf Sci 10:751–64. doi:10.3801/IAFSS.FSS.10-751.
   Google Scholar
• Lázaro, D., M. Lázaro, A. Alonso, P. Lázaro, and D. Alvear. 2019. Influence of the STA boundary conditions on thermal decomposition of thermoplastic polymers. J Therm Anal Calorim 138 (4):2457–68. doi:10.1007/s10973-019-08787-4.
   Web of Science ®Google Scholar
• Magalie, C., C. Anne-Sophie, S. Rodolphe, F. Laurent, G. Emmanuelle, and L. Christian. 2018. Fire behaviour of electrical cables in cone calorimeter: Influence of cables structure and layout. Fire Saf. J. 99:12–21. doi:10.1016/j.firesaf.2018.05.001.
   Web of Science ®Google Scholar
• Martinka, J., P. Rantuch, J. Sulová, and F. Martinka. 2019. Assessing the fire risk of electrical cables using a cone calorimeter. J Therm Anal Calorim 135 (6):3069–83. doi:10.1007/s10973-018-7556-5.
   Web of Science ®Google Scholar
• Marti, J., B. Schartel, and E. Oñate. 2022. Simulation of the burning and dripping cables in fire using the particle finite element method. J Fire Sci 40 (1):3–25. doi:10.1177/07349041211039752.
   Web of Science ®Google Scholar
• Matala, A., and S. Hostikka. 2011. Pyrolysis modelling of PVC cable materials. Fire Saf. Sci 10:917–30. doi:http://dx.doi.org/10.3801/iafss.fss.10-917.
   Google Scholar
• Matlab. 2018. Version 9.4.0.813654 (R2018a). Natick, Massachusetts: The MathWorks Inc.
   Google Scholar
• McGrattan, K., S. Hostikka, J. Floyd, R. McDermott, C. Weinschenk, and M. Vanella. 2022. Fire dynamics simulator technical reference guide volume 1: Mathematical model. National Institute of Standards and Technology-NIST Special Publication 1018 (1. doi:http://dx.doi.org/10.6028/NIST.SP.1018.
   Google Scholar
• Meinier, R., R. Sonnier, P. Zavaleta, S. Suard, and L. Ferry. 2018. Fire behavior of halogen-free flame retardant electrical cables with the cone calorimeter. J. Hazard. Mater. 342:306–16. doi:10.1016/j.jhazmat.2017.08.027.
   PubMed Web of Science ®Google Scholar
• Murer, L., S. Chatenet, G. Fontaine, S. Bourbigot, and O. Authier. 2018. Influence of model assumptions on charring polymer decomposition in the cone calorimeter. J Fire Sci 36 (3):181–201. doi:10.1177/0734904118761641.
   Web of Science ®Google Scholar
• Rhodes, B. T., and J. G. Quintiere. 1996. Burning rate and flame heat flux for PMMA in a cone calorimeter. Fire Saf. J. 26 (3):221–40. doi:10.1016/S0379-7112(96)00025-2.
   Web of Science ®Google Scholar
• UNE. 2016. Common test methods for cables under fire conditions - Heat release and smoke production measurement on cables during flame spread test - Test apparatus, procedures, results. Madrid (Spain): AENOR-Spanish Association for Standardisation and Certification.
   Google Scholar
• UNE. 2021. Reaction to fire tests for building products - building products excluding floorings exposed to the thermal attack by a single burning item. Madrid (Spain): AENOR-Spanish Association for Standardisation and Certification.
   Google Scholar
• Witkowski, A., B. Girardin, M. Försth, F. Hewitt, G. Fontaine, S. Duquesne, S. Bourbigot, and T. R. Hull. 2015. Development of an anaerobic pyrolysis model for fire retardant cable sheathing materials. Polym. Degrad. Stab. 113:208–17. doi:10.1016/j.polymdegradstab.2015.01.006.
   Web of Science ®Google Scholar
• Zhao, G., T. Beji, D. Zeinali, and B. Merci 2017. Numerical study on the influence of in-depth radiation in the pyrolysis of medium density fibreboard. In 15th International Conference Fire and Materials February 6-8 2017. San Francisco, California (USA); 863–77.
   Google Scholar