# A Coupled Thermochemical Model for Predicting Fire-Induced Thermal Responses and Decomposition Behavior

## TL;DR

This paper introduces a new model to predict how composite materials behave under fire, combining heat transfer and chemical decomposition for aerospace safety.

## Contribution

A novel coupled thermochemical model integrating heat transfer, pyrolysis kinetics, and gas dynamics for predicting fire behavior in composites.

## Key findings

- The model accurately predicts thermal responses and decomposition under fire conditions.
- Char layer insulation and heat flux attenuation are effectively captured.
- Validation against standards shows high predictive accuracy for aerospace composites.

## Abstract

Composite materials are increasingly used in aerospace applications due to their high strength-to-weight ratio, but their fire safety remains a critical concern. This study develops a coupled thermochemical model to predict the thermal response and decomposition behavior of composite materials under high-temperature fire conditions. The framework integrates heat transfer, resin pyrolysis kinetics, and gas generation dynamics, employing the Rule of Mixtures to dynamically update temperature-dependent thermophysical properties (thermal conductivity, specific heat capacity, and density). Decomposition kinetics are governed by an n-th-order Arrhenius equation, explicitly resolving the gas convection effects on energy transport. The governing equations are solved numerically using a hybrid explicit/implicit finite element scheme, ensuring stability under severe thermal gradients. Experimental validation compliant with the 14 CFR Part 25 and ISO 2685 standards demonstrates high predictive accuracy. The model successfully captures key phenomena, including the char layer insulation effects, transient heat flux attenuation, and decomposition-induced property transition. This work establishes a computational foundation for optimizing fire-resistant composites in aerospace applications, addressing critical gaps in the existing models through coupled multiphysics representation.