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Estimation of Pyrolysis Model Parameters for Solid Materials

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Estimation of pyrolysis model parameters for condensed phase materials Anna Matala, Simo Hostikka, Johan Mangs
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Page 1: Estimation of Pyrolysis Model Parameters for Solid Materials

Estimation of pyrolysis model parameters for condensed phase materials

Anna Matala, Simo Hostikka, Johan Mangs

Page 2: Estimation of Pyrolysis Model Parameters for Solid Materials

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Introduction

Page 3: Estimation of Pyrolysis Model Parameters for Solid Materials

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Small scale experiments: TGA and DSC

• Thermogravimetric Analysis (TGA) was used to determine the kinetic parameters.

• Differential Scanning Calorimetry (DSC) was used to determine the heat of reaction.

• 10-50 mg of sample material in small furnace that is heated with constant heating rate (2-20 K/min).

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Bench scale: Cone calorimeter

• Cone calorimeter results were used for estimate thermal parameters

• 10 x 10 cm sample

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Modelling thermal degradation of solids

• Kinetic parameters A, E and n depend on material, reaction scheme and value of other kinetic parameters.

• Thermal parameters k, cp, ΔH and ΔHc depend mainly on material.

• Numerical model of TGA experiment created by FDS 5.

• Parameter ranges from initial estimates or literature values.

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Genetic Algorithm (GA)

• Based on the idea of evolution: The best individuals survive.

• Selection stochastically according the difference between simulated and experimental data.

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Rules of thumb for thermal parameters

• Thermal parameters depend mainly on material, estimation range is not wide, and values listed in literature

• Possible to estimate manually

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Results: Black PMMA

• Non-charring thermoplastic that melts and burns.• Estimation was made twice using different ranges for n ([0,2] and [0,7]).

The predictions are equally accurate.• The kinetic parameter sets may be chosen among various alternatives• GA can find solution from desired range.

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Results: PVC pipe material

• Sample almost pure PVC pipe material.• Two reactions in nitrogen:

1. Release of hydrochloric acid between 200 and 300 ºC (about 54 % of the mass)2. Pyrolysis reaction with char yield at 400 ºC

• Good predictions of the PVC pyrolysis are achieved at all heating rates.

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Results: Power cable

• NOKIA AHXCMK 10 kV 3 x 95/70 mm2• Components: Sheath, insulation, filler rods, conductor• Components modelled separately• Sheath is PVC, insulation and filler PEX

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Conclusions

• Results promising: GA is an effective tool in parameter estimation and the TGA graphs can be predicted very accurately.

• HRR and MLR can be predicted accurately enough.

• Estimation process is computationally expensive.

• Kinetic parameters are model dependent and should not be considered as fundamental material properties.

• Thermal parameters are material dependent and can be estimated also manually.

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Example: Nuclear power plant cable tunnel

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Acknowledgements

• This project was part of SAFIR2010 (The Finnish Research Programme on Nuclear Power Plant Safety 2007-2010). It has been funded by State Nuclear Waste Management Fund (VYR) and VTT.

• Thermoanalytical experiments were carried out by Dr. Tuula Leskelä in Helsinki University of Technology (TKK).


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