In modern foundry industries, traditional trial-and-error methods for designing casting processes face limitations due to empirical dependencies, cost constraints, and complex production controls. Computer-Aided Engineering (CAE) has become indispensable for predicting casting feasibility and optimizing processes. This study demonstrates how MAGMASOFT® simulations enhance the development of engine cylinder block and head castings compliant with China VI emission standards, focusing on filling dynamics, solidification behavior, and material integrity.
Filling Process Simulation
Filling behavior critically impacts casting quality. Using MAGMASOFT®, we analyzed gas entrapment risks through velocity fields and temperature gradients. For engine cylinder blocks with three-layer gating systems, the initial design showed recirculation zones at flow restrictions (Figure 1a), calculated as:
$$ Re = \frac{\rho v D}{\mu} $$
where \( Re \) is Reynolds number, \( \rho \) is density, \( v \) is velocity, \( D \) is characteristic diameter, and \( \mu \) is dynamic viscosity. Turbulent flow (\( Re > 4000 \)) increased gas entrapment risks. Optimizing runner cross-sections reduced recirculation (Figure 1b), achieving laminar flow (\( Re < 2000 \)).
Velocity monitoring at critical locations ensured gating integrity:
| Location | Velocity (m/s) |
|---|---|
| Choke section | 2.8 |
| Ingate 1 | 1.1 |
| Ingate 2 | 0.9 |
Temperature field analysis revealed cold spots near oil injector bores. The modified design elevated metal temperature by 10°C through accelerated filling, governed by:
$$ Q = A \cdot v \cdot t $$
where \( Q \) is flow rate, \( A \) is cross-sectional area, and \( t \) is time.
Solidification Analysis
Solidification simulations identified shrinkage risks using liquid fraction maps. For cylinder heads, unoptimized cooling produced isolated liquid pools (Figure 6a), while chill placement improved thermal gradients (Figure 6b). The Niyama criterion predicted shrinkage porosity:
$$ Ny = \frac{G}{\sqrt{\dot{T}}} $$
where \( G \) is temperature gradient and \( \dot{T} \) is cooling rate. Regions with \( Ny < 1 \) (critical threshold) showed 93.9 mm³ shrinkage voids. Implementing sand-coated iron chills reduced defects to <1%.
Material Property Prediction
Microstructure simulations correlated process parameters with mechanical properties. For a cylinder block requiring ≥220 MPa tensile strength, initial trials showed coarse graphite at bearing cap regions due to slow cooling. Optimizing ingate dimensions accelerated solidification, refining graphite morphology. Hardness (\( H \)) and strength (\( \sigma \)) relationships followed:
$$ \sigma = 0.65H + 98 $$
Simulation vs. production results comparison:
| Parameter | Simulation | Actual |
|---|---|---|
| Hardness (HB) | 211 | 206 |
| Strength (MPa) | 253 | 244 |
Conclusion
CAE simulations enable robust process design for engine cylinder blocks and heads. Through systematic analysis of filling patterns, solidification sequences, and material properties, we achieved:
- 50% reduction in gas-related defects via velocity optimization
- 80% decrease in shrinkage porosity through chill design
- Consistent mechanical properties meeting China VI requirements
Future work will refine boundary conditions to improve simulation-practice correlation, particularly for graphite morphology effects on mechanical performance. This methodology establishes a CAE-driven framework for next-generation engine component development.