NUMERICAL SIMULATION OF FIRE SPREAD ON POLYURETHANE FOAM SLABS | NIST
Computational Fluid Dynamics (CFD) models are used extensively by fire protection engineers for performance based design and forensic analysis. The equations of motion describing the gas phase are relatively well known and the approximations in the various gas phase sub-models have been extensively studied. However, coupling of the gas phase and the condensed phase to describe flame spread over a burning solid, has proven to be difficult to model. This is due to a lack of understanding of the underlying physical phenomena that take place during the decomposition of the solid as well as poor characterization of the fundamental material properties that control the burning process. The overall goal of this project is to improve the capability of the fire models to predict flame spread over materials that typically burn in a compartment fire. In this paper, we attempt to simulate fire growth and spread on 10 cm thick slabs of polyurethane foam. A multi-layered, multi-material model was developed to simulate flame spread, and material properties were obtained from various small scale experiments. Model predictions were compared with large scale experiments on polyurethane foam slabs, ignited on one edge. Results indicate that the model is capable of qualitatively predicting the observed trends in heat release rate, flame spread rate and heat fluxes measured in the experiments. This report will describe the progress that has been made to date on modeling fire growth and spread on polyurethane foam slabs and the comparison of these results with experimental data.
Polymer surface reflectance‐absorptance characteristics
During an investigation of the time for ignition of polymeric materials under the influence of radiant heating, it was found that the polymer surface reflectance-absorptance characteristics were a major factor in the variance of the ignition times. A subsequent research study was made of the reflectance-absorptance characteristics of those polymers used in the ignition testing. Reflectance values were obtained over the wavelength of 0.3 to 2.5 microns using a double-beam Cary model 14 spectrophotometer with an integrating sphere reflectometer and over the wavelengths of 1.0 to 10.0 microns using a Gier-Dunkle Hohlraum with a Perkin-Elmer spectrophotometer. Absorptance values were obtained by means of Kirchoff's Law, 
 
 
 
Drawings and graphs are included which illustrate the test apparatus and type of data collected. A table of average absorptances of several polymers are given and listed according to the particular type of heat source used. 
 
 
 
 
 
 
Average absorptances of the polymers over the monochromatic wavelength span of the heat sources were calculated using the equation 
 
 
 
 
 
 
Mathematical analyses were developed and are presented for both the integrating sphere reflectometer and Gier-Dunkle Hohlraum unit. 
 
 
 
Drawings and graphs are included which illustrate the test apparatus and type of data collected. A table of average absorptances of several polymers are given and listed according to the particular type of heat source used.
The application of a genetic algorithm to estimate material properties for fire modeling from bench-scale fire test data
A methodology based on an automated optimization technique that uses a genetic algorithm (GA) is developed to estimate the material properties needed for CFD-based fire growth modeling from bench-scale fire test data. The proposed methodology involves simulating a bench-scale fire test with a theoretical model, and using a GA to locate a set of model parameters (material properties) that provide optimal agreement between the model predictions and the experimental data. Specifically, a GA based on the processes of natural selection and mutation is developed and integrated with the NIST FDS v4.0 pyrolysis model for thick solid fuels. The combined GA/pyrolysis model is used with cone calorimeter data for surface temperature and mass loss rate histories to estimate the material properties of two charring materials (redwood and red oak) and one thermoplastic material (polypropylene). This is done by finding the parameter sets that provide near-optimal agreement between the model predictions and experimental data, given the constraints imposed by the underlying physical model and the accuracy with which the boundary and initial conditions can be specified. The methodology is demonstrated here with the FDS pyrolysis model and cone calorimeter data, but it is general and can be used with several existing fire tests and almost any pyrolysis model. Although the proposed methodology is intended for use in CFD-based prediction of large-scale fire development, such calculations are not performed here and are recommended for future work.