PYROLYSIS MODEL PARAMETER OPTIMIZATION USING A CUSTOMIZED STOCHASTIC HILL-CLIMBER ALGORITHM AND BENCH SCALE FIRE TEST DATA

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dc.contributor.advisorTrouvé, Arnaud Cen_US
dc.contributor.authorWebster, Robert Daleen_US
dc.contributor.departmentFire Protection Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2010-02-19T07:09:08Z
dc.date.available2010-02-19T07:09:08Z
dc.date.issued2009en_US
dc.description.abstractThis study examines the ability of a stochastic hill-climber algorithm to develop an input parameter set to a finite difference one-dimensional model of transient conduction with pyrolysis to match experimentally determined mass loss rates of three sample materials exposed to a range of constant incident heat flux. The results of the stochastic hill-climber algorithm developed as part of the present study are compared to results obtained with genetic algorithms. Graphical documentation of the impact of single parameter mutation is provided. Critical analysis of the physical meaning of parameter sets, and their realistic range of application, is presented. Criteria are also suggested for stability and resolution of solid phase temperature and fuel mass loss rate in an implicit Crank-Nicolson scheme with explicit treatment of the heat generation source term.en_US
dc.identifier.urihttp://hdl.handle.net/1903/10004
dc.subject.pqcontrolledEngineering, Generalen_US
dc.subject.pqcontrolledEngineering, Mechanicalen_US
dc.subject.pqcontrolledEngineering, Materials Scienceen_US
dc.subject.pquncontrolledCrank-Nicolsonen_US
dc.subject.pquncontrolledFireen_US
dc.subject.pquncontrolledGeneticen_US
dc.subject.pquncontrolledmodelingen_US
dc.subject.pquncontrolledoptimizationen_US
dc.subject.pquncontrolledPyrolysisen_US
dc.titlePYROLYSIS MODEL PARAMETER OPTIMIZATION USING A CUSTOMIZED STOCHASTIC HILL-CLIMBER ALGORITHM AND BENCH SCALE FIRE TEST DATAen_US
dc.typeThesisen_US

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