Prediction of mass loss and heat release rates measured in cone calorimeter experiments performed on glass fiber reinforced nylon 66 blended with red phosphorus

This work demonstrates an approach to building a burning model capable of predicting combustion behavior of multicomponent flame retardant (FR) materials. Glass fiber (GF) reinforced nylon 66 (PA) blended with red phosphorus (RP) with different material compositions were selected for this work. Cone calorimeter experiments at a radiant heat flux of 50 kWm−2 were conducted to measure the mass loss rates (MLR) and heat release rates (HRR) of each formulation. It was found that with 6% red phosphorus (by weight), the peak MLR and peak HRR measured in cone calorimeter experiments were reduced significantly by 45% and 60% compared to the sample without red phosphorus, respectively. Milligram-scale flame calorimeter (MFC) was also used to measure the HRR and to calculate the effective heats of combustion of gasified products for each formulation. The previously established pyrolysis parameter sets coupled with a flame heat feedback model and with effective heats of combustion of pyrolyzates obtained based on MFC and cone calorimeter experiments, were implemented into a numerical framework, ThermaKin2Ds, to predict the burning behavior. Both the MLR and HRR of PA/GF25 (without red phosphorus) and PA/GF-RP1.5 (1.5 wt% red phosphorus) were well-captured by the model. The model overestimated the MLR and HRR profiles for PA/GF-RP6.0 (6 wt% red phosphorus). Additional simulations were performed to account for the thin char layer formed above the sample during the experiments. It was concluded that this char layer mainly acted as a thermal barrier and its role as a gas barrier was minor. The developed burning model with the inclusion of this char layer captured the burning dynamics for this blend. Note that the model enables the prediction of burning behavior of FR blends as a function of material composition and heating condition.