Phase Change Material numerical simulation: enthalpy-porosity model validation against liquid fraction data from an X-ray computed tomography measurement/system

Nowadays, Latent Thermal Energy Storage systems (LTESs) are becoming the key enabling technology for the achievement of the 2050 EU targets on energy savings and CO2 emission reduction. LTESs are based on Phase Change Materials (PCMs), which, during the liquid-solid phase change, can store and release large amount of thermal energy compared to sensible systems. Several studies have already been conducted to properly design LTESs based on PCMs and many of those aimed at developing reliable numerical tools. The main approach to model the phase change with a Computational Fluid Dynamics (CFD) approach is the enthalpy-porosity method, which has already been successfully validated in several articles, especially against the average PCM temperature. However, due to the experimental complexity, the liquid fraction evolution is hard to be measured and monitored and only symmetrical systems could have been tested so far. X-ray Computed Tomography (CT) is a strong and reliable tool to experimentally evaluate the liquid fraction profile during either the melting or solidification process in real geometries and is extremely useful to validate the numerical models. In the present study, a first attempt to combine the described experimental-numerical approach is proposed: an enthalpy-porosity model was developed and validated against liquid fraction data from a computed tomography system. The liquid fraction profile of an ice cylinder melting at ambient temperature was measured using the CT and then compared against the numerical results. The results show the promising capabilities of the proposed methodology.

Automated summary

LTESs based on PCMs are key for achieving 2050 EU energy goals. The enthalpy-porosity model using CFD has been successfully applied in several articles, but measuring the liquid fraction evolution is challenging. X-ray CT is a valuable tool for evaluating liquid fraction distribution and validating numerical models.