Experimental and numerical methodology for the analysis of fireproofing materials

Application of Graph Theory to Cost‐Effective Fire Protection of Chemical Plants During Domino Effects

“…In some cases, such as intumescent coatings or cementitious materials, phenomena of devolatilization, expansion, swelling, and so on are an inherent part of the protective action. Nevertheless, for prolonged fire exposure, the degradation and loss of effectiveness of fireproofing coatings have been documented in experimental and modeling studies . In order to account for these complicating phenomena in the graph model, it is assumed that only a limited fraction of the nominal rating time (120 min) is guaranteed with optimal performance, according to work of Landucci et al .…”

“…Nevertheless, for prolonged fire exposure, the degradation and loss of effectiveness of fireproofing coatings have been documented in experimental and modeling studies. (60,(63)(64)(65) In order to account for these complicating phenomena in the graph model, it is assumed that only a limited fraction of the nominal rating time (120 min) is guaranteed with optimal performance, according to work of Landucci et al: (45,46) -for exposure time lower than or equal to 60 min, the fireproofed tank receives no heat flux (complete shielding effect); -for exposure time higher than 60 min, it is conservatively assumed that the fireproofed tank receives the full heat load due to the fire as in the absence of fireproofing.…”

Application of dynamic Bayesian network to performance assessment of fire protection systems during domino effects

“…Due to the relevant uncertainties in gathering input data and the multiple scenarios to be analyzed within the risk assessment of industrial facilities, a conservative method was developed based on previous studies [56,57] in order to provide simple analytical functions for the temporal changes of θ. The method is described in Appendix B, with a sample application.…”

“…B.1). The model, extensively described in [57] together with the validation against experimental data, is based on a heat balance on an inorganic fireproofing board. The model allows obtaining the temperature vs time evolution of the material (e.g., T(t)), as well as the dynamic growth of thermal conductivity k(t), since the temperature variation of thermal conductivity (e.g., k(T)) is given by manufacturers and gathered in Step 1 (see Fig.…”

“…The dynamic simulation of coating behavior and available protection time was performed following the method represented in Fig. B.1, based on the application of the thermal model described in [57]. The results are reported in Fig.…”