Determination of the material parameters is one of the key challenges of numerical fire simulation attempting to predict, rather than prescribe the heat release rate. In this work, we use common fire simulation software and genetic algorithms to estimate the kinetic reaction parameters for wood components, birch wood, PVC and black PMMA. Parameters are estimated by modelling thermogravimetric experiments and minimizing the error between the experimental and numerical results. The implementation and choice of the parameters for the genetic algorithm as well as the scheme to describe wood pyrolysis are discussed.
Solid-phase pyrolysis is often modelled using the Arrhenius degradation equation with three unknown parameters: reaction order, activation energy and pre-exponential factor. Since the parameters are model dependent and not directly measurable, several estimation methods have been developed over the years for extracting them from the experimental small-scale data. Lately, the most commonly used methods have been based on optimization and curve fitting. These methods are very efficient for complex problems with multiple reactions but may require significant computational time. Direct (analytic) methods are simpler and faster but often have more restrictions and limited accuracy. This article presents a new, generalized direct method and its performance evaluated along with other commonly used estimation methods. The real usability of the methods is tested also in the presence of small noise.
The numerical modelling of solid pyrolysis for fire simulations consists of three stages: specifying the reaction scheme and physical models, estimating the kinetic and thermal parameters from experimental data, and then solving the system using a computer. The interpretation of the experimental input parameters must be verified by reproducing the experimental conditions with the same model for which the parameters are being sought. In this work, we evaluated the performance of three previously proposed reaction schemes of wood pyrolysis in reproducing thermogravimetric experiments of birch wood, and determined the remaining model parameters from micro and bench scale calorimetric experiments. The predictive capability was tested by cone calorimeter experiments at different heat fluxes. The results indicate that the first-order single-step reaction scheme can provide equally good predictions for the heat release rate as the more complex schemes. The source of the thermal parameters-direct measurement or inverse modelling-did not have a great influence on the predictive capability.
One of the most commonly used materials in electrical cables is flexible PVC. In this work, the effects of the modelling decisions and parameter estimation methods on the pyrolysis modelling of two PVC cables were studied. The kinetic and thermal parameters were estimated from TGA and cone calorimeter experiments. The role of the plasticizers was shown to be important for the early HRR. The effects of the reaction path and reaction order were only minor in the TGA results but significant effects were found in the cone calorimeter results, unless a specific set of thermal parameters was estimated. The results show that the thermal parameters estimated for one kinetic model should not be used for another, unless the kinetic models only differ in fuel yields or different pairs of kinetic coefficients with same reaction order.
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