Investigation of melting process in a PCM-based modular shell-and-coil latent thermal energy storage unit filled with coconut oil using image-processing-based techniques

This study explores the melting of coconut oil, a biodegradable phase-change material, in a shell-and-coil latent heat thermal energy storage unit under a constant heat flux of 519 W/m 2 , optimized through prior parametric studies of coil geometries and boundary conditions. A novel image processing approach, implemented via MATLAB's Image Segmenter, employs two distinct methods to analyze the melting process. The first method uses binarization to quantify the liquid fraction, revealing exponential growth that confirms convection-driven heat transfer, enhanced by coconut oil's low thermal conductivity. The second method calculates the equivalent diameter of the melting front, based on the coil's elliptical shape, to track its spatial progression. Compared to volume-averaged temperature calculations, the liquid fraction shows good initial agreement but diverges after 2000s due to image processing limitations, such as sensitivity to lighting and coil boundary effects. A theoretical model for melting front thickness was developed, though further experiments are needed for generalization. With low heat flux uncertainty this study underscores the potential of image processing for non-intrusive analysis of complex LTES geometries, advancing designs for low-temperature applications like solar thermal systems. The following study will be used to develop an enhanced and optimized model for complex geometries based on image processing techniques in the future.