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Title: Computational model of forward and opposed smoldering combustion with improved chemical kinetics
Author: Rein, Guillermo
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2005
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A computational study has been carried out to investigate smoldering ignition and propagation in polyurethane foam. The onedimensional, transient, governing equations for smoldering combustion in a porous fuel are solved accounting for improved solid-phase chemical kinetics. A systematic methodology for the determination of solid-phase kinetics suitable for numerical models has been developed and applied to the simulation of smoldering combustion. This methodology consists in the correlation of a mathematical representation of a reaction mechanism with data from previous thermogravimetric experiments. Geneticalgorithm and trail-and-error techniques are used as the optimization procedures. The corresponding kinetic parameters for two different mechanisms of polyurethane foam smoldering kinetics are quantified: a previously proposed 3-step mechanism and a new 5-step mechanism. These kinetic mechanisms are used to model one-dimensionalsmoldering combustion, numerically solving for the solid-phase and gasphase conservation equations in microgravity with a forced flow of oxidizer gas. The results from previously conducted microgravity experiments with flexible polyurethane foam are used for calibration and testing of the model predictive capabilities. Both forward and opposed smoldering configurations are examined. The model describes well both opposed and forward propagation. Specifically, the model predicts the reaction-front thermal and species structure, the onset of smoldering ignition, and the propagation rate. The model results reproduce the most important features of the smolder process and represent a significant step forward in smoldering combustion modeling.
Supervisor: Fernandez-Pello, Carlos. Sponsor: NASA
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: smoulder ; genetic algorithms ; fire ; polyurethane foam ; thermogravimetry