Phase Change Material (PCM) Melting Simulator Back
Interactive Tool — Phase Change Material

Phase Change Material (PCM) Melting Simulator

Simulate 1D melting front propagation via the enthalpy method (finite difference). Visualize phase change behavior of ice, paraffin, and molten nitrate salt with animation and comparison to the Stefan problem analytical solution.

Parameters
PCMMaterial Presets
Melting point T_melt [°C]
°C
Latent heat of fusion L_f [kJ/kg]
kJ/kg
density ρ [kg/m³]
kg/m³
Solid-phase specific heat c_p_s [J/kgK]
J/kgK
Liquid-phase specific heat c_p_l [J/kgK]
J/kgK
Solid-phase thermal conductivity k_s [W/mK]
W/mK
Liquid-phase thermal conductivity k_l [W/mK]
W/mK
Surface temperature T_s [°C]
°C
Domain Length L [mm]
mm
Results
Front position s
mm
t = 0.0 s
Click on the temperature distribution chart to set initial temperature
Melt fraction
%
Stored thermal energy
kJ/m²
Half-domain melt time
s
T(x) — Liquid (red) / Solid (blue) / Front (dashed)
Front position s(t) vs √t — Comparison with Stefan analytical solution (straight line)
Enthalpy H(x) distribution — Latent heat plateau visualization

What is Phase Change Material (PCM) Analysis?

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What exactly is a Phase Change Material, and why is it tricky to simulate its melting?
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Basically, a PCM is a substance that absorbs or releases a huge amount of energy when it changes phase, like ice melting into water. The tricky part is that the boundary between solid and liquid—the melting front—moves over time. In this simulator, we use the "enthalpy method" to track this moving front without explicitly chasing it, which is a common CAE technique. Try selecting a different material preset above, like switching from ice to paraffin, and see how the melting behavior changes instantly.
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Wait, really? The simulator doesn't track the front directly? So what is it actually calculating?
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Exactly! Instead of tracking the sharp interface, the enthalpy method calculates a smoothed "mushy zone" where material is partially melted. It solves for temperature and total enthalpy (which includes the latent heat). For instance, in the chart, you see the temperature plateau at the melting point while enthalpy keeps rising—that's the latent heat being absorbed. Slide the "Latent Heat of Fusion (L_f)" parameter and watch how much longer that temperature plateau becomes for the same applied surface heat.
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That makes sense. So the different thermal properties for solid and liquid phases must be super important. How do they affect the result?
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Great question! They control how fast heat travels to the melting front and how fast the melted material can carry heat away. A common case is paraffin wax: its liquid conductivity ($k_l$) is much lower than its solid conductivity ($k_s$). This can create a "bottleneck" where the melted layer acts as an insulator! Try it: set the "Liquid Conductivity (k_l)" much lower than the solid value and see the melting slow down dramatically after an initial burst.

Physical Model & Key Equations

The core of the simulation is the 1D heat conduction equation, reformulated using enthalpy (H) to naturally incorporate the phase change. The governing equation solved at each node in the finite difference grid is:

$$\rho \frac{\partial H}{\partial t}= \frac{\partial}{\partial x}\left( k(T) \frac{\partial T}{\partial x}\right)$$

Here, $\rho$ is the density (which you can set), $H$ is the total enthalpy per unit mass, $t$ is time, $k(T)$ is the temperature-dependent thermal conductivity, and $T$ is temperature. The key is that enthalpy $H$ includes both sensible and latent heat.

The relationship between enthalpy and temperature defines the phase change. It's a piecewise function that creates the "mushy zone":

$$ H(T) = \begin{cases}c_{p,s}\cdot T & T < T_m \\ c_{p,s}\cdot T_m + L_f \cdot \phi + c_{p,l}\cdot (T - T_m) & T = T_m \\ c_{p,s}\cdot T_m + L_f + c_{p,l}\cdot (T - T_m) & T > T_m \end{cases}$$

Where $T_m$ is the melting point, $L_f$ is the latent heat of fusion, $c_{p,s}$ and $c_{p,l}$ are the specific heats for solid and liquid, and $\phi$ is the liquid fraction (between 0 and 1). This is why you see a jump in the enthalpy plot—it's the latent heat $L_f$ being added at $T_m$.

Frequently Asked Questions

There are three types: ice (water), paraffin, and nitrate molten salt. The physical properties (density, thermal conductivity, latent heat, melting point, etc.) of each material are preset and can be selected from a dropdown menu.
The analytical solution of the Stefan problem (theoretical curve of the melting front position) is overlaid on the simulation result graph. This allows visual confirmation of the calculation accuracy of the enthalpy method.
Yes, you can adjust the animation playback speed using the slider on the screen. It is also possible to pause or manually step forward, allowing detailed observation of temperature distribution and phase state at specific times.
It is useful for designing latent heat storage materials and understanding the fundamentals of freezing and melting processes. For example, it can be used for predicting the heat storage performance of building materials containing paraffin, or for preliminary studies of heat transport analysis in solar thermal power generation using molten salt.

Real-World Applications

Building Thermal Management: Paraffin-based PCMs are integrated into wallboards or ceiling tiles. They melt during the day, absorbing excess heat to keep a room cool, and solidify at night, releasing the stored heat. This simulator helps engineers size the PCM layer thickness and select the optimal melting temperature based on local climate.

Electronic Device Cooling: High-performance electronics generate intense, intermittent heat bursts. A PCM package attached to a CPU can absorb this heat during a spike, preventing thermal throttling, while giving fans and heat sinks more time to dissipate the energy. The conductivity values (k_s, k_l) are critical design parameters here.

Concentrated Solar Power (CSP): Molten salts (like the preset in the simulator) are used as both heat transfer fluid and thermal storage medium in CSP plants. They store solar energy as latent heat during the day to generate steam and electricity at night. Accurate simulation of their melting/freezing cycles is essential for plant efficiency and reliability.

Food Processing & Cold Chain: In shipping containers for temperature-sensitive pharmaceuticals or food, ice or other PCMs are used as thermal buffers. The simulation helps predict how long the payload will stay within the safe temperature range based on the PCM's properties and the external ambient temperature (set by the "Surface Temperature T_s" parameter).

Common Misunderstandings and Points to Note

When you start using this simulator, there are a few points beginners often stumble on. A major misconception is the idea that simply increasing the latent heat will improve performance. While it's true that a larger melting latent heat L_f increases thermal storage capacity, if the thermal conductivity k is low, heat struggles to penetrate deep into the material, preventing you from utilizing that capacity. For example, paraffin has high latent heat but low thermal conductivity (about 0.2 W/mK). Try comparing "Thermal Conductivity k" values of 0.1 and 0.5 in the tool. You'll see that even with the same latent heat, the speed of heat transfer is completely different, significantly altering the half-domain melting time. In practice, you often need to incorporate fins or metal matrices to enhance thermal conductivity.

Next, consider the realism of boundary condition settings. This tool uses the simple condition of a "constant surface temperature." However, in real applications like building walls, external air temperature fluctuates with solar radiation, and convective heat transfer cannot be ignored. Simulating with a fixed "Surface Temperature T_s" in the tool is a good first step, but for actual design, you need to consider boundary conditions of the third kind (convective boundary conditions). Try settings that rapidly raise and lower the surface temperature to get a feel for the difference from reality.

Finally, understand the limitations of the 1D model. This calculation assumes shapes where one-dimensional heat flow is dominant, like slabs or infinitely long cylinders. Real thermal storage units experience three-dimensional heat spreading and the effects of natural convection. This is why when you select "Ice" to melt in the tool, it melts differently than an actual block of ice. Remember, this tool is for understanding basic principles and checking parameter sensitivity; more advanced simulation is needed for detailed design.

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