Thermo-Kinetic Model of Burning for Polymeric Materials

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Thermo-Kinetic Model of Burning for Polymeric Materials Stanislav I. Stoliarov a, Sean Crowley b, Richard Lyon b a University of Maryland, Fire Protection Engineering, College Park, MD 20742 b FAA W. J. Hughes Technical Center, Egg Harbor Twp., NJ 08405

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Key Long-Term Objectives Develop a versatile model for simulation of bench-scale flammability tests. Parameterize this model for various types of polymeric materials. Relate parameters (properties) used in the model to molecular structure.

Flammability Measurement Techniques Cone Calorimetry (heat release measurement) Fire Propagation Apparatus (heat release measurement) Gasification Apparatus (mass loss measurement)

Flammability Measurement Techniques Cone Calorimetry (heat release measurement) Fire Propagation Apparatus (heat release measurement) Gasification Apparatus (mass loss measurement)

ThermaKin Model Overview radiation convection heat flux = f (component flux) Gas phase is represented by empirical relations between heat flux and component fluxes. The relations are derived from experiments. component flux (key predicted quantity) radiative loss conduction A B + C Condensed phase is represented by a mixture of components (A, B, C), which interact chemically and physically.

Radiative Energy Transfer During any given time step, the external radiation is absorbed by a single element chosen at random. Iiix probability of absorption I radiative loss T i 4 i internal radiative flux k r T 1 3 i T x 1 2 i external radiation radiative loss internal radiative flux

Mass Transfer Components are categorized as solids, liquids, or gases. mg/ g V mass flux of gas g x Swelling factor g defines volumetric reaction of the condensed phase to the presence of gases. gas flux g = 0 gas flux g = 1

Chemical Reactions q A A + q B B q C C + q D D + heat Aexp rate or Aexp E RT E RT m V m V A A m V B Bubble Dynamics (example) melt small bubble nucleation small bubble + small bubble medium bubble small bubble + medium bubble large bubble growth The reaction can be switched on or off at a specified temperature. bubble immobile bubble immobile bubble bubble transport

Parameterization ThermaKin Models of Poly(methylmethacrylate) (PMMA) High-impact polystyrene (HIPS) High-density polyethylene (HDPE) Bisphenol A polycarbonate (PC) Temperature dependences of densities (from literature) Temperature dependences of heat capacities and heat of melting (from DSC measurements) Kinetics and heat of decomposition (from TGA and DSC measurements) Emissivities and absorption coefficients (from literature) Temperature dependences of thermal conductivities (from Thermoflixer measurements)

Kinetics of Decomposition Assumptions: PMMA Gas + heat MLR = k D m PMMA (first order) Gas leaves PMMA instantaneously.

Modeling of Fire Calorimetry Experiments External Radiative Heat, 23-92 kw m -2 (up to 15% correction for sample expansion) Flame Heat, 11-24 kw m -2 (turned on when the mass flux reaches 20 kw m -2 equivalent of heat release) Before-ignition Convective Loss, 10 W m -2 K -1 Polymer Sample Insulator (Kaowool) 3-25 mm 15 mm Zero Mass Flow Boundary Zero Heat Flow Boundary

Gasification Conditions: external heat flux = 52 kw m -2 initial sample thickness 9 mm PMMA HIPS HDPE Experiment Model

Cone Calorimetry Conditions: external heat flux = 49 kw m -2 initial sample thickness 9 mm PMMA Model heat flame of heat combustion flux = 12 of kw gases m -2 = 24 kj g -1

Cone Calorimetry of PMMA increasing thickness (3 25 mm) increasing heat flux (23 75 kw m -2 )

Cone Calorimetry of HIPS increasing thickness (3 25 mm) increasing heat flux (23 75 kw m -2 )

Cone Calorimetry of HDPE increasing thickness (3 25 mm) increasing heat flux (23 75 kw m -2 )

Cone Calorimetry of PC Flame heat flux = 15 kw m -2. The main mode of heat transfer inside char is radiation. The rate of transfer is defined by a single adjustable parameter. 5 mm PC sample after 160 s at 75 kw m -2.

Sensitivity of Peak and Average Mass Loss Rates

Conclusions A one-dimensional numerical pyrolysis model can be used to predict the outcome of fire calorimetry experiments performed on polymeric materials. The predictions require the knowledge of chemical, thermal, and optical properties of the material. Measurement of these properties represents a challenging task. The rate of decomposition (defined by A and E), heat of decomposition, char yield and heat of combustion are the key parameters required for prediction of the peak and average heat release rates. p