Uncertainties in modelling heat transfer in fire resistance tests: A case study of stone wool sandwich panels

Abstract

Summary Modelling fire performance of building fire barriers would allow optimising the design solutions before performing costly fire resistance tests and promote performance‐based fire safety engineering. Numerical heat conduction analysis is widely used for predicting the insulation capability of fire barriers. Heat conduction analysis uses material properties and boundary condition parameters as the input. The uncertainties in these input parameters result in a wide range of possible model outcomes. In this study, the output sensitivity of a heat conduction model to the uncertainties in the input parameters was investigated. The methodology was applied to stone wool core sandwich panels subjected to the ISO 834 standard fire resistance temperature/time curve. Realistic input parameter value distributions were applied based on material property measurements at site and data available in literature. A Monte Carlo approach and a functional analysis were used to analyse the results. Overall, the model is more sensitive to the boundary conditions than to the material thermal properties. Nevertheless, thermal conductivity can be identified as the most important individual input parameter.

Multiphysics Modelling of Stone Wool Fire Resistance

“…Due to the uncertainties in the fire conditions and stone wools material properties, the fire performance evaluation needs to be probabilistic [12,13]. We estimate the probabilistic cold-side temperatures considering the fire condition and stone wool material as the input stochastic.…”

Response of stone wool–insulated building barriers under severe heating exposures

“…Numerical studies have shown how a limited variation in stone wool density might have a lesser impact on the unexposed side temperature in standard ISO 834 exposures, compared to variation in the thermal conductivity. 35,36 Comparing test I to test J for G-SW-G composites (Tables 1 and 2), the stone wool density was 47% higher and the thermal conductivity was 2% lower. Furthermore, test G had a 39% higher density and a 10% lower ambient thermal conductivity compared to test H for S-SW-S composites.…”

Meta-model based stochastic simulation of fire barrier cold-side temperature

“…The barrier thermal resistance evaluation is not merely a deterministic problem, due to the uncertainties associated with the fire conditions and barrier material properties, which vary between production batches and, especially, between different products and brands [30,31,32,33]. The uncertainties are handled through sensitivity studies [35,34], the use of safety factors such as Best Estimate Plus Introduction Uncertainty (BEPU) [36] or probabilistic analysis [30].…”