In recent years, the demand for lightweight materials in industries such as automotive and aerospace has driven significant research into magnesium alloys, particularly ZM5 alloy, due to its excellent strength-to-weight ratio. Lost wax investment casting, a precision casting method, is widely used for producing complex components with high dimensional accuracy. This study investigates the formability of ZM5 alloy under various cooling mediums—air cooling, oil cooling, and water cooling—in the context of lost wax investment casting. We employ numerical simulations and experimental validations to analyze temperature distributions, isolated liquid phase regions, and porosity defects. The goal is to provide technical insights for optimizing cooling strategies in practical lost wax investment casting processes.
The ZM5 alloy, with its composition detailed in Table 1, was selected for this study due to its common application in lightweight structures. Using UG 3D modeling software, we developed a geometric model of the casting, which was then imported into ProCAST for numerical simulation. The simulations were conducted under three cooling conditions: air cooling, oil cooling, and water cooling, with key parameters such as pouring temperature set at 720°C and mold preheat temperature at 350°C. The interfacial heat transfer coefficient between the casting and mold was determined through inverse heat conduction analysis, ensuring accurate representation of the lost wax investment casting process.
| Element | Content |
|---|---|
| Mg | Remainder |
| Zn | 0.63 |
| Al | 8.77 |
| Mn | 0.26 |
| Si | 0.015 |
| Fe | 0.002 |
| Ni | 0.001 |
| Cu | 0.001 |
| Be | 0.004 |
| Other single elements | ≤ 0.1 |
The thermophysical properties of ZM5 alloy, crucial for accurate simulation in lost wax investment casting, are summarized in Table 2. These parameters include liquidus and solidus temperatures, thermal conductivity, specific heat capacity, and density, which influence the solidification behavior under different cooling mediums. The finite element model, with a shell thickness of 7 mm made of mullite sand, was meshed into 64478 surface elements and 517231 volume elements to ensure precise calculations.
| Parameter | Value |
|---|---|
| Liquidus Temperature (K) | 603 |
| Solidus Temperature (K) | 418 |
| Thermal Conductivity (W·m⁻¹·K⁻¹) | 72–105 |
| Specific Heat Capacity (kJ·kg⁻¹·K⁻¹) | 0.95–1.04 |
| Density (kg·m⁻³) | 1524–1810 |
In lost wax investment casting, the filling process is critical for defect prevention. We simulated the filling sequence over time, observing that initial stages exhibited turbulent flow, potentially leading to gas entrapment and slag inclusions. As filling progressed, the liquid metal stabilized, with even distribution across the mold cavity. This behavior underscores the importance of controlled filling in lost wax investment casting to minimize defects. The temperature evolution during solidification was analyzed using ProCAST, with the heat transfer governed by Fourier’s law: $$ q = -k \nabla T $$ where \( q \) is the heat flux, \( k \) is the thermal conductivity, and \( \nabla T \) is the temperature gradient. This equation highlights how cooling mediums affect heat dissipation in lost wax investment casting.
Under air cooling, the temperature distribution gradient was the smallest, resulting in slower solidification rates. In contrast, water cooling exhibited the widest temperature gradient, facilitating rapid heat extraction. Oil cooling showed intermediate behavior. These differences are quantified by the cooling rate \( \frac{dT}{dt} \), which can be expressed as: $$ \frac{dT}{dt} = \frac{-h A (T – T_{\infty})}{\rho V c_p} $$ where \( h \) is the heat transfer coefficient, \( A \) is the surface area, \( T \) is the temperature, \( T_{\infty} \) is the ambient temperature, \( \rho \) is density, \( V \) is volume, and \( c_p \) is specific heat capacity. This formula illustrates why water cooling, with its higher \( h \), leads to faster solidification in lost wax investment casting.
The isolated liquid phase regions, which indicate potential shrinkage defects, varied significantly with cooling mediums. In air cooling, these regions formed ellipsoidal shapes, whereas oil and water cooling produced needle-cone shapes. This variation is linked to the solidification time \( t_s \), given by: $$ t_s = \frac{L^2}{\alpha \cdot \text{Ste}} $$ where \( L \) is a characteristic length, \( \alpha \) is thermal diffusivity, and Ste is the Stefan number. Shorter solidification times in water cooling promote finer microstructures, reducing defect sizes in lost wax investment casting.
Porosity analysis revealed that microshrinkage volumes were similar across cooling conditions at a criterion of 2%, but their locations aligned with isolated liquid phase regions. The Niyama criterion, often used in lost wax investment casting simulations, relates local thermal conditions to porosity: $$ Ny = \frac{G}{\sqrt{R}} $$ where \( G \) is the temperature gradient and \( R \) is the cooling rate. Lower Niyama values indicate higher porosity risk, which was observed in regions with poor feeding during solidification.
Experimental validation under air cooling involved temperature measurements using K-type thermocouples placed at distances of 80 mm, 180 mm, and 280 mm from the sprue. The temperature-time curves matched simulations closely, with a maximum deviation of 6°C, confirming the reliability of the lost wax investment casting model. X-ray imaging of cast specimens showed porosity distributions consistent with simulations, though slight shape variations occurred due to practical mold temperature deviations. This alignment validates the use of numerical simulations for optimizing lost wax investment casting processes.
In conclusion, this study demonstrates that cooling mediums significantly influence the formability of ZM5 alloy in lost wax investment casting. Water cooling provides the most extensive temperature gradients and rapid solidification, reducing defect sizes, while air cooling results in slower processes with larger isolated regions. The integration of simulation and experiment offers a robust framework for selecting appropriate cooling strategies in lost wax investment casting, enhancing product quality and efficiency. Future work could explore additional alloys or advanced cooling techniques to further improve lost wax investment casting applications.