Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-052099-131146


Document Typedissertation
Author NamePehrson, Richard
URNetd-052099-131146
TitlePrediction of Fire Growth on Furniture Using CFD
DegreePhD
DepartmentFire Protection Engineering
Advisors
  • Dr. Jonathan Barnett, Advisor
  • Dr. Brian J. Savilonis, Committee Member
  • Dr. Nicholas Dembsey, Committee Member
  • Howard Professor Emeritus Howard W. Emmons, Committee Member
  • Keywords
  • fire growth
  • furniture
  • CFD
  • Date of Presentation/Defense1999-04-19
    Availability unrestricted

    Abstract

    A fire growth calculation method has been developed that couples a computational fluid dynamics (CFD) model with bench scale cone calorimeter test data for predicting the rate of flame spread on compartment contents such as furniture. The commercial CFD code TASCflow has been applied to solve time averaged conservation equations using an algebraic multigrid solver with mass weighted skewed upstream differencing for advection.

    Closure models include k-epsilon for turbulence, eddy breakup for combustion following a single step irreversible reaction with Arrhenius rate constant, finite difference radiation transfer, and conjugate heat transfer. Radiation properties are determined from concentrations of soot, CO2 and H2O using the narrow band model of Grosshandler and exponential wide band curve fit model of Modak. The growth in pyrolyzing area is predicted by treating flame spread as a series of piloted ignitions based on coupled gas-fluid boundary conditions. The mass loss rate from a given surface element follows the bench scale test data for input to the combustion prediction. The fire growth model has been tested against foam-fabric mattresses and chairs burned in the furniture calorimeter. In general, agreement between model and experiment for peak heat release rate (HRR), time to peak HRR, and total energy lost is within pm 20%. Used as a proxy for the flame spread velocity, the slope of the HRR curve predicted by model agreed with experiment within pm 20% for all but one case.

    Files
  • pehrson.pdf

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