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Journal of Thermal Analysis and Calorimetry

, Volume 138, Issue 4, pp 2703–2713 | Cite as

LLDPE kinetic properties estimation combining thermogravimetry and differential scanning calorimetry as optimization targets

  • Alain AlonsoEmail author
  • Mariano Lázaro
  • Pedro Lázaro
  • David Lázaro
  • Daniel Alvear
Article
  • 137 Downloads

Abstract

Thermal analysis techniques play a crucial role to characterize solid-phase thermal decomposition, since it provides information about how mass is lost (thermal gravimetric analysis) and energy released [differential scanning calorimetry (DSC)]. However, most of the input thermal parameters and kinetic properties to be used in fire computer modelling cannot be obtained directly from those tests. Early works looked forward achieving those parameters employing indirect fitting methods, which enable the user to obtain a set of parameters capable of simulating accurately the mass loss curve (TG) or its derivative (DTG). This work aims to study the possibility of adding the energy released as a new target in the process, applying the analysis to linear low-density polyethylene. Results obtained in the present work reveal the major challenge of getting a set of parameters that can also fit DSC curve. The level of accuracy of the fitting to TG curve is higher than to DSC curve. This fact increases the value of the errors when both curves are used as targets to approach. As a result, this paper includes an alternative to consider the effects of the DSC curve.

Keywords

Thermal analysis Thermal decomposition Fire computer models Optimization methods LLDPE 

List of symbols

A

Pre-exponential factor (s−1)

Ea

Activation energy (kJ kmol−1)

n

Reaction order

Hr

Heat of reaction (kJ kg−1)

r

Reaction rate at temperature T

T

Temperature (°C)

ρ

Density (kg m−3)

Cp

Specific heat (kJ kg−1 K−1)

k

Conductivity (W m−1 K−1)

ε

Emissivity

η

Absorption coefficient (m−1)

\(Y_{{{\text{s}},{\text{i}}}}\)

Quotient between density of the material at temperature T and the initial density

\(r_{\text{ij}}\)

Reaction rate (kg s−1)

\(v_{{{\text{si}}^\prime {\text{j}}}}\)

Yield produced by the reaction i

\(r_{{{\text{i}}^\prime {\text{j}}}}\)

Residue produced by the reaction i

α

Coefficient of the conversion factor of reactant/-

TG

Thermogravimetric analysis

STA

Simultaneous thermal analysis

DTG

Derivative thermogravimetric analysis

MLR

Mass loss rate

DSC

Differential scanning calorimetry

FPA

Fire Propagation Apparatus

M

Reacting material

P

Submaterial generated as the product of the reaction

F

Fuel gas released by the reaction

G

Non-burning gas released by the reaction

R

Residue produced by the reaction

νp

Amount of submaterial produced

νf

Amount of fuel gas released

νg

Amount of non-burning gas released

νr

Amount of residue produced

\(X_{\text{error}}^{\text{curve}}\)

Error between experimental and simulated curves

γ

Influence of the TG curve over global error

β

Influence of the DSC curve over global error

Notes

Acknowledgements

The authors would like to thank to the Consejo de Seguridad Nuclear for the cooperation and co-financing the project “Simulation of fires in nuclear power plants” and to CAFESTO Project funded by the Spanish Ministry of Science, Innovation and Universities and the Spanish State Research Agency through public–private partnerships (Retos Colaboración 2017 call, ref RTC-2017-6066-8) co-funded by ERDF under the objective “Strengthening research, technological development and innovation”.

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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2019

Authors and Affiliations

  1. 1.GIDAI, University of CantabriaSantanderSpain

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