Methodology for material property determination

Predicting solid material pyrolysis requires numerous parameters/properties that are time consuming and difficult to measure. Multiobjective optimization techniques have been used to determine these parameters; however, a methodology for the types of tests needed for the optimization and parameters that should be optimized versus measured has not been fully established. This study investigated combinations of testing protocols and parameters for optimization to determine a testing and optimization methodology that results in the accurate parameters. A Shuffled Complex Evolution (SCE) optimization routine was used to determine parameters based on some parameters being known (ie, measured) and others being determined through optimization and different combinations of types of input data. The results indicate that material testing should be done at three different heating rates in a thermogravimetric analyzer (TGA) and at three different heat fluxes in the cone calorimeter. The TGA tests and two cone calorimeter tests are input into the SCE optimization routine to determine the remaining parameters. The third cone calorimeter test is used to validate the parameters determined using the methodology. The method provides parameters within 20% of the actual parameters input into the Fire Dynamics Simulator (FDS) virtual experiment models. This method is applied to Polymethyl methacrylate (PMMA) experimental data to prove effectiveness.