The present study focuses on the casting process design and optimization of an aluminum alloy turbine volute for an aviation turbofan engine. Due to the complex geometry, thin-walled sections, and internal hollow passages, the component is highly susceptible to casting defects such as shrinkage porosity, gas porosity, misruns, and cold shuts. To address these challenges, a comprehensive approach combining theoretical analysis, numerical simulation with ProCAST, actual production trials, and post-casting heat treatment was adopted. The objective is to establish a systematic and scientific methodology to minimize casting defects while ensuring mechanical performance and production efficiency. The study demonstrates that the integration of simulation-driven process design can significantly improve casting quality and reduce trial-and-error costs.
The turbine volute is one of the core components in an aircraft turbine engine. It must withstand high temperatures, high pressures, and corrosive environments while maintaining high strength and low weight. The component features a maximum overall dimension of 167 mm × 150 mm × 160.35 mm, with the thinnest wall section being only 3 mm. The internal structure contains multiple intersecting hollow passages, which creates complex heat transfer and solidification behavior. Such geometry makes the casting process extremely challenging. Traditional empirical trial-and-error methods are time-consuming and costly, especially for precision aerospace castings. Therefore, the use of computational simulation tools has become essential to predict and mitigate potential casting defects before physical production.
This research employs the ProCAST numerical simulation software, which is based on the finite element method (FEM). ProCAST allows for the coupled simulation of mold filling, solidification, and defect prediction. The software provides a comprehensive platform for virtual prototyping, enabling engineers to evaluate different gating systems, riser designs, and cooling strategies. In this work, the alloy used is ZAlSi5CuMgA (ZL105A), a high-strength aluminum-silicon-copper-magnesium alloy. The chemical composition is listed in Table 1.
| Si | Cu | Mg | Ti | Al |
|---|---|---|---|---|
| 4.50–5.50 | 1.00–1.50 | 0.40–0.60 | 0.08–0.20 | Balance |
The liquidus and solidus temperatures were determined using the Lever Rule solidification model within ProCAST. The calculated liquidus temperature is 625.9°C and the solidus temperature is 551.6°C. These values are critical for setting the pouring temperature and designing the feeding system.
1. Numerical Simulation Methodology
The numerical simulation of the casting process involves solving the governing equations for fluid flow, heat transfer, and solidification. In ProCAST, the mold filling process is modeled as incompressible viscous flow, governed by the continuity, momentum, and energy conservation equations. These equations are discretized using the finite element method on an unstructured mesh. The continuity equation is expressed as:
$$ \frac{\partial \rho}{\partial t} + \nabla \cdot (\rho \vec{V}) = 0 \tag{1} $$
where \(\rho\) is the density of the liquid metal, \(\vec{V}\) is the velocity vector, and \(t\) is time. For incompressible flow, this simplifies to:
$$ \nabla \cdot \vec{V} = 0 \tag{2} $$
The momentum conservation equation, also known as the Navier-Stokes equation, is written in three-dimensional Cartesian coordinates:
$$ \rho \left( \frac{\partial u}{\partial t} + u \frac{\partial u}{\partial x} + v \frac{\partial u}{\partial y} + w \frac{\partial u}{\partial z} \right) = -\frac{\partial p}{\partial x} + \mu \left( \frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2} \right) + \rho g_x \tag{3} $$
where \(u\), \(v\), \(w\) are the velocity components, \(p\) is the pressure, \(\mu\) is the dynamic viscosity, and \(g_x\) is the gravitational acceleration component. The energy equation accounts for heat transfer and phase change:
$$ \rho c_p \left( \frac{\partial T}{\partial t} + u \frac{\partial T}{\partial x} + v \frac{\partial T}{\partial y} + w \frac{\partial T}{\partial z} \right) = \frac{\partial}{\partial x} \left( \lambda \frac{\partial T}{\partial x} \right) + \frac{\partial}{\partial y} \left( \lambda \frac{\partial T}{\partial y} \right) + \frac{\partial}{\partial z} \left( \lambda \frac{\partial T}{\partial z} \right) + Q \tag{4} $$
In the above equation, \(c_p\) is the specific heat, \(T\) is temperature, \(\lambda\) is thermal conductivity, and \(Q\) is the heat source term due to latent heat release during solidification, expressed as \(Q = \rho L \frac{\partial f_s}{\partial t}\), where \(L\) is the latent heat and \(f_s\) is the solid fraction.
Heat transfer at the mold-metal interface is modeled using a heat transfer coefficient (HTC). The interface heat flux is given by Newton’s law of cooling:
$$ q = \alpha (T_f – T_w) \tag{5} $$
where \(\alpha\) is the interface heat transfer coefficient, \(T_f\) is the fluid temperature, and \(T_w\) is the wall temperature. For radiation, the Stefan-Boltzmann law is applied:
$$ q = \varepsilon \sigma_0 T_s^4 \tag{6} $$
where \(\varepsilon\) is the emissivity, \(\sigma_0\) is the Stefan-Boltzmann constant, and \(T_s\) is the surface absolute temperature.
2. Initial Casting Process Design
Based on the structural analysis of the turbine volute, the initial casting position was chosen with the large diameter at the top and the small diameter at the bottom. This orientation promotes sequential solidification from the bottom to the top, with risers placed at the top to feed the last solidifying regions. The initial gating system was designed as a bottom-filled system comprising a vertical sprue, two horizontal runners, and ingates. The pouring temperature was set to 800°C, and the filling time was targeted at 10 seconds. Four cylindrical risers with a diameter of 40 mm and height of 60 mm were symmetrically placed around the top flange. The total cross-sectional area of a single riser was 1761.65 mm². These parameters are summarized in Table 2.
| Parameter | Value |
|---|---|
| Gating system | Bottom-filled, horizontal runner |
| Pouring temperature | 800°C |
| Filling time | 10 s |
| Number of risers | 4 |
| Riser type | Waist-shaped (modified) |
| Riser cross-sectional area | 1761.65 mm² |
| Mold material | Alkaline phenolic resin-bonded sand |
| Interface HTC (metal-mold) | 500 W/(m²·K) |
Before performing the simulation, a 3D model of the turbine volute was created using Unigraphics NX 12.0. The model was then imported into ProCAST for mesh generation. A uniform mesh was used with a size of 3 mm for the main casting and 10 mm for the gating system. The final mesh contained approximately 260,000 surface elements and 1,700,000 volume elements.
3. Simulation Results of Initial Design and Defect Prediction
3.1 Filling Process Analysis
The filling behavior of the initial design was evaluated through transient simulation. The results indicated that at t = 2.17 s, the liquid aluminum reached the ingate. At t = 3.08 s, the flow velocity was excessively high, causing jetting and entrapment of air, which is a primary source of gas porosity. By t = 4.53 s, the liquid front was uneven and tilted, indicating unbalanced filling. These phenomena are detrimental because they promote casting defects such as gas porosity, oxide inclusions, and cold shuts. The filling process was completed at t = 10.17 s when the fill ratio reached 98%. The observed filling defects are summarized in Table 3.
| Time (s) | Observation | Potential Defect |
|---|---|---|
| 2.17 | Liquid reaches ingate | – |
| 3.08 | High velocity jetting, air entrainment | Gas porosity, oxide inclusions |
| 4.53 | Uneven liquid front, tilting | Cold shut, misrun |
| 8.65 | Mold almost filled | – |
| 10.17 | Filling complete | – |
3.2 Solidification and Shrinkage Defects
The solidification analysis of the initial design revealed that the central thin-walled region solidified first, while the protruding pipe mouth on the middle side solidified much later. This non-uniform solidification leads to isolated liquid pools that are difficult to feed, resulting in shrinkage porosity. The Niyama criterion was employed to predict micro-porosity. The Niyama parameter \(Ny\) is defined as:
$$ Ny = \frac{G}{\sqrt{R}} \tag{7} $$
where \(G\) is the temperature gradient and \(R\) is the cooling rate. Low values of \(Ny\) indicate a high probability of shrinkage porosity. In this study, a threshold of 15% probability was considered. The simulation showed significant shrinkage porosity in the central hollow intersection region, as well as an annular distribution at the bottom thick section. These regions are characterized by thicker sections compared to the surrounding thin walls, making them thermally isolated.
The total shrinkage porosity prediction, based on the Chvorinov modulus method, was used to predict macro-shrinkage cavities. The Chvorinov rule is given by:
$$ t_{sol} = K \left( \frac{V}{A} \right)^2 \tag{8} $$
where \(t_{sol}\) is the solidification time, \(V\) is the volume, \(A\) is the surface area, and \(K\) is a constant related to mold material and thermal properties. The simulation results showed prominent shrinkage cavities in the center of the casting and at the protruding pipe mouth. The presence of these defects indicates that the initial design does not provide adequate feeding, and the gating/riser system needs improvement.
4. Improved Casting Process Design
Based on the simulation outcomes, several modifications were implemented to reduce casting defects and improve filling and solidification behavior. These modifications include:
4.1 Auxiliary Side Runners
Two auxiliary side runners were added to the existing horizontal runners to distribute the melt more evenly into the mold cavity. Each auxiliary runner has a contact surface of 20 mm × 4 mm and is shaped as an inclined trapezoidal body. A parametric study was conducted to determine the optimal thickness of the side runners. Simulation results at t = 2.5 s for different thicknesses showed that 4 mm provided the most uniform flow, with both the main and auxiliary runners delivering metal simultaneously without disturbing the mold filling.
4.2 Pouring Temperature Optimization
Nine different pouring temperatures were evaluated: 640, 660, 680, 700, 720, 740, 760, 780, and 800°C. The simulations showed that temperatures below 720°C resulted in incomplete filling and premature solidification, while temperatures above 760°C increased the risk of shrinkage due to higher liquid contraction. The optimal pouring temperature was set to 740°C, with a corresponding mass flow rate of 0.6097 kg/s.
4.3 Cold Iron Placement
To control the solidification sequence and reduce hot spots, nine cold irons were placed in locations corresponding to predicted hot spots. The cold irons were made of steel and were in direct contact with the casting. The interface heat transfer coefficient between the casting and the cold iron was set to 2000 W/(m²·K), while that between the mold and the cold iron was set to 800 W/(m²·K). The placement of cold irons accelerated the cooling of thick sections, promoting a more uniform solidification and reducing the risk of shrinkage porosity.
4.4 Riser and Gating System Size Optimization
An additional riser was added at the central protruding pipe mouth to provide feeding for this thick, isolated region. The new riser has a cross-sectional area of 2310.31 mm². The overall gating system dimensions were recalculated to minimize material waste while maintaining adequate filling. The final dimensions were: sprue diameter 64.5 mm, vertical runner diameter 30 mm, and horizontal runner cross-section 31.45 mm × 31.45 mm. The improved process parameters are summarized in Table 4.
| Parameter | Value |
|---|---|
| Pouring temperature | 740°C |
| Mass flow rate | 0.6097 kg/s |
| Number of auxiliary runners | 2 |
| Auxiliary runner contact area | 20 mm × 4 mm |
| Number of risers | 5 |
| Additional riser area | 2310.31 mm² |
| Number of cold irons | 9 |
| Vertical runner diameter | 30 mm |
| Horizontal runner cross-section | 31.45 mm × 31.45 mm |
5. Simulation Results of Improved Design
5.1 Filling Process
The improved filling simulation showed that the melt entered the cavity smoothly through both the main and auxiliary runners, without jetting or air entrapment. At t = 2.74 s, the four streams of metal merged gently. The liquid front remained level and rose steadily, with no tilting observed. The fill ratio reached 98% at t = 9.57 s, and the stratification was parallel and uniform. This confirms that the auxiliary runners effectively reduced the filling velocity and promoted a calm, progressive filling pattern, which is essential for minimizing casting defects such as gas porosity and oxide films.
5.2 Solidification Process
The improved solidification simulation demonstrated that the central protruding pipe mouth solidified at a much faster rate compared to the initial design, thanks to the additional riser and cool iron effects. The three smaller protrusions also solidified in sync with the surrounding structure. A desired sequential solidification pattern was achieved, with the risers feeding the casting until the final stages. This reduces the risk of shrinkage cavities and ensures a sound casting.
5.3 Defect Prediction Comparison
Table 5 compares the defect prediction results between the initial and improved designs. The percentage area of shrinkage porosity in the casting decreased by over 70%, while the area of shrinkage cavities decreased by over 90%. The remaining shrinkage porosity was confined to the risers and gating system, where it is harmless after cutting off.
| Defect Type | Initial Design | Improved Design | Reduction |
|---|---|---|---|
| Shrinkage porosity area | Extensive | Very low | >70% |
| Shrinkage cavity area | Large cavities in casting | Only in risers/runners | >90% |
6. Production Validation
Based on the improved process design, actual turbine volute castings were produced using 3D-printed sand molds and gravity pouring. The molds were printed in segments and assembled before pouring. The pouring temperature was maintained at 740°C, and the pouring time was 10 seconds. After solidification, the molds were left undisturbed for about 20 hours to avoid thermal cracking. The castings were then cleaned, with the internal sand cores removed by high-temperature roasting and high-pressure water rinsing. Figure 1 shows an example of a cast cylinder block, which is also typical of complex aluminum alloy castings. The manufactured turbine volute castings were examined by X-ray inspection, which revealed no casting defects such as porosity, shrinkage, cracks, or misruns. The alloy composition was verified by optical emission spectroscopy, and the results conform to the national standard GB/T 16865—2013.
7. Heat Treatment and Mechanical Properties
To meet the mechanical property requirements, the castings were subjected to a T5 heat treatment (solution treatment and artificial aging). The optimized heat treatment schedule is listed in Table 6.
| Process | Parameters |
|---|---|
| Solution temperature | 535°C |
| Solution time | 6 h |
| Heating rate | ≤3°C/min |
| Quenching medium | Water at 25°C |
| Quenching transfer time | ≤25 s |
| Aging temperature | 170°C |
| Aging time | 8 h |
| Cooling | Air cooling to room temperature |
Tensile tests were performed on standard specimens machined from separately cast test bars. Three groups (S1, S2, S3) were subjected to solution times of 2 h, 4 h, and 6 h, respectively, while the aging treatment was identical. The results are summarized in Table 7.
| Group | Ultimate tensile strength (MPa) as-cast | Ultimate tensile strength (MPa) heat-treated | Yield strength Rp0.2 (MPa) | Elongation after fracture (%) |
|---|---|---|---|---|
| S1 | 183.3 | 239.6 | 179.3 | 3.7 |
| S2 | 181.9 | 279.8 | 195.7 | 2.2 |
| S3 | 184.1 | 333.6 | 274.1 | 1.7 |
Only the S3 group (6 h solution treatment) met the national standard requirement of tensile strength ≥280 MPa. The improvement in tensile strength is approximately 81.2% compared to the as-cast value. The elongation decreased with longer solution time, indicating that the heat treatment increased strength at the expense of ductility, which is typical for precipitation-hardened aluminum alloys.
Brinell hardness tests were also performed, using a 5 mm hardened steel ball and a load of 1226 N. The results are shown in Table 8.
| Group | As-cast hardness (HB) | Heat-treated hardness (HB) | Increase (%) |
|---|---|---|---|
| S1 | 58.31 | 92.65 | 58.9 |
| S2 | 59.02 | 103.48 | 75.3 |
| S3 | 58.63 | 107.24 | 82.9 |
All heat-treated samples exceeded the minimum specified hardness of 80 HB. The hardness increased progressively with solution time, although the incremental gain diminished after 4 hours, indicating that 6 hours is sufficient and near-optimal.
8. Microstructural Characterization
Optical microscopy (OM) was used to examine the microstructure of the alloy before and after the T5 treatment. In the as-cast condition, the microstructure consisted of primary α-Al dendrites with large plate-like and blocky eutectic silicon (Si) particles distributed in the α matrix. There were also small amounts of Al₂Cu phase. The coarse, segregated eutectic Si seriously disrupted the continuity of the α solid solution and reduced mechanical properties.
After the optimized T5 treatment, the eutectic silicon particles were fragmented and their edges became blunt. The size of the Si particles decreased and their distribution became more uniform, forming a network along the α-Al boundaries. This microstructural change is the main reason for the significant improvement in tensile strength and hardness. The Al₂Cu phase was dissolved into the α matrix, leaving only trace amounts, which contributes to precipitation hardening during aging.
Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) were performed on heat-treated samples. The EDS analysis confirmed that the matrix was aluminum, with silicon segregated in localized regions and a very small amount of copper. The presence of oxygen was attributed to surface contamination. The fracture surfaces of the tensile specimens were also observed by SEM. All specimens exhibited brittle fracture with cleavage facets and tear ridges. A few dimples were found on the tear ridges, indicating limited localized plastic deformation. The heat-treated specimens showed shallower dimples and more pronounced tear ridges compared to the as-cast specimens, consistent with their higher strength and lower ductility.
9. Conclusions
In this work, a comprehensive casting process design and optimization for an aluminum alloy turbine volute was conducted using numerical simulation and experimental validation. The key findings can be summarized as follows:
- The initial gating design, with a high pouring temperature of 800°C and only four risers, led to turbulent filling and inadequate feeding, resulting in significant casting defects such as gas porosity, shrinkage porosity, and shrinkage cavities.
- By adding two auxiliary side runners, reducing the pouring temperature to 740°C, placing nine cold irons, and adding a fifth riser at the critical thick section, the filling became smooth and sequential solidification was achieved.
- The improved process reduced the predicted shrinkage porosity area by more than 70% and shrinkage cavity area by more than 90%, with remaining defects confined to the risers and gating system.
- Actual production using the improved process produced castings free of defects, as confirmed by X-ray inspection and composition analysis.
- A T5 heat treatment consisting of solution treatment at 535°C for 6 hours, quenching in water at 25°C, and aging at 170°C for 8 hours resulted in a tensile strength increase from 184.1 MPa to 333.6 MPa (an 81.2% increase) and a Brinell hardness increase from 58.63 HB to 107.24 HB (an 82.9% increase), while meeting the national standard requirements.
- Microstructural analysis revealed that the heat treatment refined the eutectic silicon phase and increased the continuity of the α solid solution, which is the main reason for the enhanced mechanical properties.
This study demonstrates that the combination of numerical simulation, systematic process optimization, and experimental verification is an effective approach to reduce casting defects and improve the quality of complex aluminum alloy castings. The methodology can be readily extended to other precision casting applications in the aerospace and automotive industries.