This study investigates the optimization of casting parameters for ZG15Cr2Mo1 heat-resistant steel casting used in high-pressure steam chambers through numerical simulation and orthogonal experimental design. The research focuses on reducing shrinkage porosity and cavity defects in sand mold gravity casting while maintaining structural integrity under extreme thermal conditions.
1. Methodology
The casting process optimization for steel castings combines numerical simulation with orthogonal experimental design. The three-dimensional model of the steam chamber was created using SolidWorks, with critical dimensions of 1648mm × 620mm × 1077mm and weight of 1957.8kg. The ProCAST simulation platform analyzed the filling and solidification processes through finite element method (FEM).
The governing equations for solidification analysis include:
$$ \frac{\partial (\rho H)}{\partial t} + \nabla \cdot (\rho u H) = \nabla \cdot (k \nabla T) $$
Where ρ represents density, H enthalpy, u velocity vector, k thermal conductivity, and T temperature.
| C | Mn | Si | Cr | Mo | S | P |
|---|---|---|---|---|---|---|
| ≤0.18 | 0.40-0.70 | ≤0.60 | 2.00-2.75 | 0.90-1.20 | ≤0.030 | ≤0.030 |
2. Orthogonal Experimental Design
A three-factor three-level orthogonal array was developed to optimize steel casting parameters:
| Level | A: Pouring Temperature (°C) | B: Pouring Speed (kg/s) | C: Number of Gates |
|---|---|---|---|
| 1 | 1580 | 115 | 2 |
| 2 | 1600 | 120 | 3 |
| 3 | 1620 | 125 | 6 |
The shrinkage porosity percentage (P) was calculated using:
$$ P = \frac{V_{\text{defect}}}{V_{\text{total}}} \times 100\% $$
Where Vdefect represents the volume of shrinkage defects and Vtotal the total casting volume.
3. Results and Discussion
The orthogonal experiment results revealed significant parameter influences on steel casting quality:
| Test | A | B | C | Porosity (%) |
|---|---|---|---|---|
| 1 | 1 | 1 | 1 | 3.44 |
| 2 | 1 | 2 | 2 | 2.74 |
| 3 | 1 | 3 | 3 | 4.38 |
| 4 | 2 | 1 | 2 | 2.79 |
| 5 | 2 | 2 | 3 | 4.44 |
| 6 | 2 | 3 | 1 | 2.81 |
| 7 | 3 | 1 | 3 | 4.55 |
| 8 | 3 | 2 | 1 | 2.81 |
| 9 | 3 | 3 | 2 | 2.78 |
The range analysis showed the influence order of parameters on steel casting quality:
$$ R_C (1.689) > R_B (0.268) > R_A (0.173) $$
indicating gate number as the most significant factor. The optimal parameters were determined as A2B3C2 (1600°C pouring temperature, 125kg/s pouring speed, and 3 gates).
4. Process Optimization
The optimized steel casting process demonstrated significant improvement:
$$ \text{Porosity reduction} = \frac{2.834\% – 1.025\%}{2.834\%} \times 100\% = 63.8\% $$
Key solidification parameters were calculated using:
$$ t_{\text{solidification}} = \frac{(T_{\text{pour}} – T_{\text{solidus}})^2}{\pi k \rho c} $$
Where tsolidification is solidification time, k thermal diffusivity, ρ density, and c specific heat capacity.
5. Conclusion
This research establishes an effective methodology for optimizing steel casting processes through orthogonal experimental design and numerical simulation. The proposed parameters significantly reduce shrinkage defects in high-pressure steam chamber castings while maintaining production efficiency. Future work should investigate the combined effects of riser design and chilling techniques on large-section steel castings.