Phase Change Materials (PCMs) are a new innovative idea in thermal energy storage systems. They are able to absorb, store, and release huge amounts of energy during their phase change processes, mostly when they melt and solidify. These materials use the idea of latent heat storage, which says that energy can be taken in or given off at almost steady temperature during phase change. This gives them a much higher energy density than other sensible heat storage methods. To get the most out of PCM-based thermal management systems in a wide range of situations, including controlling the temperature in buildings, cooling gadgets, and storing solar thermal energy, you need to fully understand these complex multiphysics processes. This research carefully checks if a computational fluid dynamics (CFD) model VALIDATES the experimental benchmark data from Gau and Viskanta’s (1986) groundbreaking work.

• Reference [1]: Assis, E., et al. “Numerical and experimental study of melting in a spherical shell.” International Journal of Heat and Mass Transfer9-10 (2007): 1790-1804.
• Reference [2]: Ghosh, Debasree, and Chandan Guha. “Numerical and experimental investigation of paraffin wax melting in spherical cavity.” Heat and Mass Transfer5 (2019): 1427-1437.

Figure 1: The computational domain of spherical shell [1]

Simulation Process

The computing domain was made to be an exact copy of the experimental setup mentioned in Gau and Viskanta’s study. To get a good picture of the steep temperature differences and changing melt interface, the geometry was broken up using a high-resolution structured grid and selective refinement close to the walls. The Solidification and Melting model in ANSYS Fluent was used to handle the phase change physics, and the Volume of Fluid (VOF) method was used to keep track of the different phases and how the contact changed over time. The simulation was run with a carefully chosen time-step size to make sure numerical stability while capturing transient melting behavior. The model was run for a total of 900 seconds.

Post-processing

The melt fraction evolution graph shows exceptional agreement between our CFD simulation and the experimental data, with the numerical predictions (square markers) closely tracking the measured values (triangular markers) throughout the entire 900-second melting process. The simulation accurately captures the initial rapid melting phase (0-200 seconds) where conduction dominates heat transfer, followed by the more gradual, nearly linear progression from 200-900 seconds when natural convection becomes increasingly influential. At the 600-second mark, our predicted melt fraction of 0.55 deviates by less than 2% from the experimental value of 0.54, validating the model’s ability to accurately balance the competing heat transfer mechanisms. This close correlation confirms that our numerical approach correctly implements the enthalpy-porosity technique for phase change modeling and properly accounts for the buoyancy-driven flows that develop in the liquid region.

Figure 2: Melt fraction VALIDATION of PCM Melting In Spherical Shell CFD Simulation

The temperature contours and flow pathlines show the complicated thermal structures that form during the melting process, which is more proof that the model is physically correct. The temperature graph clearly shows a distinct stratification pattern, with the solid PCM’s blue core (300K) getting smaller as it’s surrounded by the melted area, which has a temperature gradient from the melting point (302.78K) to the hot boundary (321K). The asymmetric melting pattern with clear convective cells in the upper part of the domain stands out. This is where the simulation correctly shows the Rayleigh-Bénard instabilities that happen when warmer liquid rises along the heated wall and cooler fluid falls near the phase interface.

Figure 3: PCM Melting validation against experimental data