4.6 Article

An Investigation towards Coupling Molecular Dynamics with Computational Fluid Dynamics for Modelling Polymer Pyrolysis

期刊

MOLECULES
卷 27, 期 1, 页码 -

出版社

MDPI
DOI: 10.3390/molecules27010292

关键词

combustion; computational fluid dynamics; detailed chemistry; flame retardants; molecular dynamics; pyrolysis

资金

  1. Australian Research Council (ARC Industrial Training Transformation Centre) [IC170100032]
  2. Australian Government Research Training Program Scholarship

向作者/读者索取更多资源

A multi-scale modelling framework was proposed in this study to simulate the pyrolysis process of polymer composites using Molecular Dynamics models and Computational Fluid Dynamics fire model. The results showed the potential application of the developed model in predicting toxic gas emissions during polymer decomposition.
Building polymers implemented into building panels and exterior facades have been determined as the major contributor to severe fire incidents, including the 2017 Grenfell Tower fire incident. To gain a deeper understanding of the pyrolysis process of these polymer composites, this work proposes a multi-scale modelling framework comprising of applying the kinetics parameters and detailed pyrolysis gas volatiles (parent combustion fuel and key precursor species) extracted from Molecular Dynamics models to a macro-scale Computational Fluid Dynamics fire model. The modelling framework was tested for pure and flame-retardant polyethylene systems. Based on the modelling results, the chemical distribution of the fully decomposed chemical compounds was realised for the selected polymers. Subsequently, the identified gas volatiles from solid to gas phases were applied as the parent fuel in the detailed chemical kinetics combustion model for enhanced predictions of toxic gas, charring, and smoke particulate predictions. The results demonstrate the potential application of the developed model in the simulation of different polymer materials without substantial prior knowledge of the thermal degradation properties from costly experiments.

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