Fire resistive materials (FRMs) perform a critical function in building safety by protecting steel components from high temperature conditions during a fire or multi-hazard exposure. These materials generally delay the transfer of energy from the ongoing fire to the steel via a combination of a low thermal conductivity and a variety of endothermic reactions, such as dehydration and decarbonation of cementitious and gypsum-based binders. In addition to heat transfer through the FRM by conduction, at higher temperatures, transfer by radiation also makes a substantial contribution to material performance. Radiation transfer in a porous material is influenced by both overall porosity and by the size and shape of the individual "pores" (Russell, 1935; Loeb, 1954).
Currently, FRMs are evaluated and certified based mainly on their ability to limit the temperature rise of the substrate steel when exposed in a furnace to a standard temperature rise curve (ASTM E119; ASTM, 2004). The FRMs are thus rated for a specific period of time for protecting a specific member of the steel construction, e.g., a 2 h rating for protecting beams or a 3 h rating for protecting columns. The E119 test is strictly pass/fail and as such does not truly quantify material performance. Furthermore, it is extremely difficult to extrapolate E119 test results to real fire scenarios. Clearly, the development of new FRMs and an increased understanding of the thermal performance of existing ones would benefit greatly from a materials science-based approach to characterizing these materials.
Recently (Bentz et al., 2004), it has been suggested that to characterize FRMs with respect to thermal performance m odels, measurements/calculations of the following thermophysical properties are required: thermal conductivity, density, heat capacity, and any enthalpies of reactions or phase changes occurring in the temperature range of interest. This paper focuses on a computational approach to estimating thermal conductivity based on a detailed analysis of the three-dimensional microstructure of the FRMs. Such an approach may provide a viable alternative to the expensive and often difficult measurement of thermal conductivity at elevated temperatures for these dynamic materials. Additionally, the approach should provide valuable insights into the microstructural features that most influence thermal performance, so that existing products may be optimized and new ones formulated with minimal effort.
The basic approach is to capture the three-dimensional microstructure of FRMs at sub-millimeter resolution using x-ray microtomography. Image processing and finite difference computer programs are then utilized to extract the key microstructural features (pores) and determine their influence on the thermal conductivity as a function of material temperature. Finally, the computational results are compared to experimental measurements performed on the same materials to both evaluate the accuracy of the computational approach and to identify areas where improvements are needed.