Thermal characterization of passive fire protection coatings using Bayesian inference

Abstract

Structural members made of steel are frequently used in the construction of buildings because of their superior mechanical properties and execution times. To avoid the structure collapse in the event of a fire, it is imperative that the entire building and all of its components have the appropriate fire resistance due to the degradation of mechanical properties with temperature. Utilizing greater cross-sectional steels is one strategy for designing structures with the necessary fire resistance. The thermal resistance period can be extended by using passive fire protection coatings, which shield the structural members from the impacts of the high temperatures produced by a fire. Typically, a commercial coating's fire resistance is assessed by applying expensive standard test methods such as EN 13381-4 and EN 1363-1. These tests are costly, time-consuming, and require numerous tests to cover the variety of structural members and paint thicknesses. Instead, using a modeling strategy based on the intumescent paint's thermal properties could offer a useful tool to simplify the testing process and aid in the creation of fire-resistant structures. Therefore, understanding the equivalent/effective thermal conductivity of the intumescent paint is essential to forecast how a steel structure will react to fire when painted with intumescent paint. In this chapter, various methods reported for the thermal characterization of passive fire protection coatings are discussed. Also, this chapter explains about the Bayesian inference, which is an emerging statistical technique in estimating thermal properties of a material with the help of measured temperature data. Using this method, not only thermal parameters of an intumescent paint are estimated but also uncertainties associated with those calculated. A case study is presented to demonstrate the efficacy of Bayesian inference in the field of thermal characterization of passive fire protection coatings. This method can be used as an alternative where it is difficult to organize experiments for the class of complex geometries and requires highly configured computation facility and time for the full numerical simulations.