An experimental investigation on kinetic analysis of thermal degradation of shape stable composite phase change materials and adaptive neuro fuzzy inference system modeling for predicting mass loss

The thermal stability of a shape stable composite phase change material (SSCPCM) has been investigated using a thermogravimetric analyser. X-ray diffraction, Scanning Electron Microscope, Fourier transform infrared, Brunauer-Emmett-Teller, and Differential Scanning Calorimeter analysis are used to characterize the PCM and SSCPCM. The activation energy of PCM and SSCPCM is estimated using multiple value model-free methods, namely, Friedman, Kissinger-Akahira-Sunose, Starink, Ozawa-Flynn-Wall, and Vyazovkin. The SSCPCM exhibits 4.96, 6.95, 6.76, 8.02, and 4% higher activation energy than the pure PCM as determined by the Friedman, KAS, OFW, Vyazovkin, and Starink methods, respectively. The degradation temperature of SSCPCM improved by 12.86, 7.85, and 10.41%, compared to PCM, at a heating rate of 5,10, and 15 degrees C min(-1), respectively. ANFIS modeling is used in this study to predict the degradation of PCM and SSCPCM. The mass loss (%) of PCM and SSCPCM samples is predicted by considering the input parameters as PCM type, temperature, and heating rate of the sample. It is found that the combination of a generalized bell-shaped input and a linear output membership function is best suitable for predicting the mass loss. The developed hybrid ANFIS model very well predicts the experimental mass loss of the SSCPCM with a coefficient of determination (R-2) of 0.99.