Estimating Effective Material Thermal Properties for Use in CFAST

Abstract

A material thermal property database was developed for use in Consolidated Model of Fire and Smoke Transport (CFAST) simulations performed in support of fire investigations. The database includes thermal properties for interior surface materials; ignition, metal, and plastic target materials; and damage target materials. CFAST assumes that thermal properties of interior surface and target materials remain constant throughout the course of the fire. In reality, these properties vary with temperature. Assuming ambient temperature properties remain constant may result in significant errors in the heat conduction calculations. This paper presents the results of Fire Dynamics Simulator (FDS) compartment fire simulations to evaluate the effect on room temperature predictions of using constant versus temperature-dependent thermal properties for the gypsum board on walls and ceiling. The simulations show that assuming ambient temperature properties will overestimate the room temperature during the peak burning and decay periods of the fire. Fidelity of the predictions can be improved by increasing the specific heat in the constant property simulations to account for the gypsum dehydration energetics indirectly. The paper describes methodologies developed to estimate effective constant thermal properties for ignition and metal target materials and provides examples to illustrate their application. The methodology for ignition target materials relies on FDS heat conduction simulations of a series of ignition experiments conducted in the Cone Calorimeter. An evolutionary method is used to obtain values for thermal conductivity, specific heat, and ignition temperature that optimize agreement between calculated and measured ignition times. The approach to estimate effective thermal properties of metal target materials is similar. First, FDS and temperature-dependent property values of the metal are used to determine the time for the target surface to reach the melting point for a range of heating conditions. Next, an evolutionary optimization method is used to estimate constant property values that result in best-fitting FDS target temperature rise predictions.