Thermal degradation studies and hybrid neural network modelling of eutectic phase change material composites

Abstract

Summary Using a thermogravimetric analyzer, the thermal stability of pure eutectic phase change material (PEPCM) (LiNO3 + NaCl) and composite eutectic PCM (CEPCM) mixture (ie, PCM containing 9% expanded graphite [EG]) was examined. PEPCM and CEPCM degradation kinetics were studied using model free kinetics methods. The activation energy of both PCM samples was evaluated using the Kissinger‐Akahira‐Sunose (KAS), Flynn‐Wall‐Ozawa (FWO), Starink, Friedman and Vyazovkin kinetic models. The calculated activation energies for Vyazovkin, Frideman, Ozawa, KAS and Starink techniques for PEPCM were 80.62‐149.2, 108.1‐180.18, 83.74‐136.17, 73.55‐127.02 and 74.64‐149.9 kJ/mol, respectively. Likewise, the activation energy of CEPCM vary between 59.4‐161.41, 83.97‐188.69, 57.1‐147.32, 54.19‐137.43 and 55‐160.65 kJ/mol. Hybrid neural networks such as ANN‐PSO and ANFIS were used to model the degradation of PCM samples. The type of PCM, the heating rate, and the temperature were applied as input parameters, while the sample's mass loss was utilized as an output parameter. The created hybrid models are capable of effectively predicting experimental TGA data.

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