In this work, I investigated the casting process of a divided axle housing used in the load-bearing axle of a tractor. The axle housing is a critical structural component that must withstand high impact loads under fully loaded conditions across plateaus, saline-alkali soils, deserts, and other complex terrains. The original sand mold casting process suffered from a shrinkage porosity and shrinkage cavity defect rate as high as 70%, leading to oil leakage and oil seepage during service. The annual economic loss exceeded one million RMB. My objective was to design, simulate, optimize, and experimentally validate a robust sand mold casting process that eliminates these internal defects and improves the air tightness of the axle housing.
The axle housing is made of ZG40Mn low-alloy cast steel. The overall dimensions are approximately 452 mm × 340 mm × 396 mm, with an average wall thickness of 25 mm. The maximum wall thickness is 29 mm, and the minimum is 15 mm. The internal cavity and the flange face are the most critical regions because they must remain leak-free under pressure. The complex geometry, large wall thickness variation, and high shrinkage of cast steel make sand mold casting particularly challenging. I therefore combined theoretical analysis, three-dimensional modeling, finite element simulation, and physical experiments to develop an optimized process.
Sand mold casting is a versatile and cost-effective process for producing complex steel components. In this study, I used water-glass sand mold casting because it is suitable for multi-variety and small-batch production, and it is especially appropriate for complex axle housings. However, the gravity pouring nature of sand mold casting and the complex structure of the axle housing increase the risk of shrinkage defects. To address this, I designed three different gating systems, simulated the filling and solidification behavior using Procast, and optimized the feeding and chilling systems.
I began by analyzing the structural and process characteristics of the axle housing. The material ZG40Mn was selected because it provides a good balance of strength, toughness, and wear resistance. Its chemical composition and mechanical properties are summarized in the following tables.
| Element | C | Mn | Si | S | P |
|---|---|---|---|---|---|
| ZG40Mn | 0.35–0.45 | 1.0–1.5 | 0.35–0.45 | ≤0.03 | ≤0.03 |
| Material | Heat Treatment | Yield Strength (MPa) | Tensile Strength (MPa) | Elongation (%) | Reduction of Area (%) | Hardness (HB) |
|---|---|---|---|---|---|---|
| ZG40Mn | Normalizing + Tempering | ≥295 | ≥640 | ≥12 | ≥30 | 163–200 |
For sand mold casting of this steel, the raw materials must be strictly controlled. I selected scrap steel, ferrosilicon, high-carbon ferromanganese, and silicon-aluminum-iron alloy as the main charge materials. The scrap steel was inspected for shape, size, and surface cleanliness. Ferrosilicon (FeSi75A11.5-B) was used to adjust silicon content, and high-carbon ferromanganese (FeMn68C7.0) was used to adjust manganese content. Silicon-aluminum-iron alloy served as a deoxidizer to improve steel cleanliness. The silica sand used for the mold and core had to meet GB/T 9442-1998, with controlled grain shape and minimal impurities.
The pouring position and parting surface were determined to ensure the internal cavity and flange face achieve high quality. I selected a horizontal pouring position with the middle pouring system. This arrangement allows smooth filling, reduces sand scouring, and facilitates mold parting and core setting. The parting surface was set at the middle plane, consistent with the pouring position, to minimize core shifting and mold damage.
The pouring temperature was optimized by simulating three values: 1540 °C, 1560 °C, and 1580 °C. The temperature history curves showed that at 1580 °C, the metal cools rapidly during filling, which promotes complete filling, while the later solidification stage proceeds more slowly, reducing thermal stress and hot crack tendency. Therefore, I selected a pouring temperature of 1580 °C. The pouring time was calculated using the empirical formula for cast steel:
$$ t = C \sqrt{G_L} $$
where \( G_L \) is the weight of liquid metal flowing through the choke, and \( C \) is a coefficient. For this axle housing, the casting weight is approximately 117 kg, and the liquid metal weight is about 108 kg. Using \( C = 0.8 \), the pouring time was determined to be about 10 s.
The casting process parameters were then established. The dimensional tolerance grade was selected as CT12 according to GB6414-1999. The linear shrinkage rate for cast steel was taken as 2%, based on the free and restrained shrinkage behavior. The core design included horizontal and vertical core prints to accurately position the core. The horizontal core print length was 50 mm on each side with a draft of 3°, and the vertical core print lengths were 50 mm for the upper and 30 mm for the lower, with drafts of 4° and 1°, respectively. The draft angle for the pattern was set to 3° for the 18 mm high reinforcing ribs.
| Alloy Type | Restrained Shrinkage (%) | Free Shrinkage (%) |
|---|---|---|
| Carbon and low-alloy steel | 1.3–1.7 | 1.6–2.0 |
| Molding Method | Pattern Height (mm) | Draft Angle |
|---|---|---|
| Hand molding | <20 | 3°–5° |
| Hand molding | 20–50 | 2°–3° |
| Hand molding | >50–100 | 1°30′–2° |
| Hand molding | >100–200 | 0°45′–1°30′ |
| Hand molding | ≥200 | 0°30′–1°30′ |
The original casting process used a bottom pouring system and suffered from a high defect rate. I therefore redesigned the gating system using three different types: closed, open, and semi-closed. The gating system design began with the determination of the ingate position. Based on the structural features, I selected a middle pouring system, which combines the advantages of top and bottom pouring. The average static head was calculated to ensure complete filling:
$$ h_M = L \tan \alpha $$
where \( L \) is the horizontal distance from the highest point of the casting to the sprue center, and \( \alpha \) is the pressure angle. With \( L = 320 \) mm and \( \alpha = 10^\circ \), the minimum residual head \( h_M \) was 56 mm. The sprue height must therefore be at least 246 mm.
The choke area was calculated using the pouring rate method. The formula for the choke area is:
$$ A = \frac{G_L}{t k S’} $$
where \( G_L = 108 \) kg, \( t = 10 \) s, \( k = 0.6 \) kg/(cm²·s), and \( S’ = 0.8 \). The calculated choke area was 22.5 cm², which corresponds to an ingate diameter of 54 mm. I then designed three gating systems with different area ratios.
| Gating System Type | Advantages | Disadvantages |
|---|---|---|
| Closed | Easy to fill, good slag retention, low metal consumption, easy cleaning | High flow velocity, strong scouring, prone to splashing |
| Open | Smooth filling, low scouring force | Poor slag retention, high metal consumption, difficult cleaning |
| Semi-closed | Good slag retention, smoother than closed, lower scouring than closed | Fills slightly later than closed |
For the closed gating system, the area ratio was:
$$ \sum A_{\text{ingate}} : \sum A_{\text{runner}} : \sum A_{\text{sprue}} = 1 : 1.3 : 1.5 $$
The ingate area was 22.5 cm², the runner area was 29.25 cm², and the sprue area was 33.75 cm².
For the open gating system, the area ratio was:
$$ \sum A_{\text{ingate}} : \sum A_{\text{runner}} : \sum A_{\text{sprue}} = 1.2 : 1.1 : 1 $$
The ingate area was 22.5 cm², the runner area was 21 cm², and the sprue area was 18.8 cm².
For the semi-closed gating system, the area ratio was:
$$ \sum A_{\text{ingate}} : \sum A_{\text{runner}} : \sum A_{\text{sprue}} = 1 : 0.8 : 1.2 $$
The ingate area was 22.5 cm², the runner area was 18 cm², and the sprue area was 27 cm².
| Scheme | Ingate Area (cm²) | Runner Area (cm²) | Sprue Area (cm²) | Area Ratio |
|---|---|---|---|---|
| Scheme 1: Closed | 22.5 | 29.25 | 33.75 | 1 : 1.3 : 1.5 |
| Scheme 2: Open | 22.5 | 21 | 18.8 | 1.2 : 1.1 : 1 |
| Scheme 3: Semi-closed | 22.5 | 18 | 27 | 1 : 0.8 : 1.2 |
I used Procast finite element analysis software to simulate the filling and solidification processes. The three-dimensional models were created in Creo and imported into Procast. The mesh size for the axle housing was 6 mm, and the runner mesh size was 15 mm. A virtual sand box was used. The thermal physical properties of ZG40Mn were taken from the Procast database, using the Lever algorithm for thermal conductivity. The initial temperatures were 1580 °C for the melt and 30 °C for the sand mold. The interfacial heat transfer coefficients are listed below.
| Interface | Heat Transfer Coefficient (W/(m²·K)) |
|---|---|
| Casting–Mold | 350–500 |
| Casting–Air | 350–500 |
| Casting–Chromite Sand | 500–700 |
| Casting–Insulating Sleeve | 50–150 |
| Casting–Chill | 1000–3000 |
The filling process simulation revealed distinct flow behaviors for the three schemes. In Scheme 1, the metal flowed smoothly and the runners remained full, but slag retention was only moderate. In Scheme 2, the flow was unstable, with isolated metal streams and a high risk of cold shuts and sand inclusions. In Scheme 3, the flow was the most stable, the runners stayed full, and slag retention was excellent. The solidification fractions during filling are compared in the following table.
| Scheme | Initial Fill 25% | Early-Mid Fill 30% | Mid-Late Fill 64% | Late Fill 96% | Result |
|---|---|---|---|---|---|
| Scheme 1: Closed | 0 | 0 | 2.5 | 10.4 | Smooth flow |
| Scheme 2: Open | 0 | 0.1 | 10.5 | 18.8 | Turbulence, large temperature variation |
| Scheme 3: Semi-closed | 0 | 0 | 4 | 12.7 | Gentle flow |
The temperature field simulation showed the evolution of solid fraction and isolated liquid regions. In all three schemes, isolated liquid zones formed in the late solidification stage, which are prone to shrinkage defects. The comparison is summarized below.
| Scheme | Initial Solidification (%) | Early Solidification (%) | Mid-Late Solidification (%) | Late Solidification (%) | Result |
|---|---|---|---|---|---|
| Scheme 1: Closed | 8.6 | 16.7 | 74 | 86 | Small isolated liquid zone |
| Scheme 2: Open | 30 | 50 | 78.9 | 92.6 | Volume deficit at final stage |
| Scheme 3: Semi-closed | 24 | 69 | 77.3 | 82.7 | Smallest isolated liquid zone |
Shrinkage cavity and porosity are the most critical defects. Shrinkage cavities form because of volume deficits in hot spots that cannot be fed by liquid metal. Shrinkage porosity is a dispersed form of micro-shrinkage. In cast steel, the high shrinkage rate makes feeding essential. The simulation showed that Scheme 2 produced the largest isolated liquid zones and the most severe shrinkage defects, so it was eliminated. Scheme 1 and Scheme 3 were further optimized by adding risers and chills.
The modulus of the axle housing was calculated to design the riser:
$$ M = \frac{V}{A} $$
where \( V \) is the volume and \( A \) is the heat-dissipating surface area. The calculated modulus was 9.7 mm. The riser diameter and height were designed using:
$$ D_r = (1.2 \sim 2) \delta_c $$
$$ H_r = (1.0 \sim 1.5) D_r $$
where \( \delta_c \) is the wall thickness at the hot spot. I selected a riser diameter of 80 mm and a riser height of 150 mm. The riser modulus was 18.75 mm, which is greater than the casting modulus, ensuring effective feeding. Blind risers were placed at the ingate, and open risers were placed on the upper surface of the axle housing. Chills were placed in the internal cavity and at thick sections to promote directional solidification. The chills were made of cast steel with dimensions of approximately 30 mm × 50 mm × 60 mm, and their surfaces were cleaned to remove oxide layers.
After adding risers and chills, I re-ran the Procast simulation for Scheme 1 and Scheme 3. The optimized results showed that Scheme 1 still had residual shrinkage porosity near the cylindrical cavity close to the flange. Scheme 3, however, eliminated the shrinkage defects entirely; the porosity was transferred to the risers, and the hot spots were properly fed. This confirmed that the semi-closed gating system with optimized risers and chills is the best process.
| Scheme | Flow Field Result | Late Solidification Fraction | Defect Prediction | After Adding Risers and Chills | Conclusion |
|---|---|---|---|---|---|
| Scheme 1: Closed | Smooth flow, moderate slag retention | 86%, fast solidification | Local shrinkage | Local shrinkage not eliminated | Rejected |
| Scheme 2: Open | Slow flow, difficult filling, poor slag retention | 92%, local fast solidification | Large-area shrinkage | Rejected | Rejected |
| Scheme 3: Semi-closed | Most stable flow, excellent slag retention | 82%, uniform solidification | Local shrinkage | Shrinkage eliminated | Best |
The final optimized sand mold casting process uses a semi-closed gating system. The pouring temperature is 1580 °C, and the pouring time is 10 s. One mold produces one casting. The gating system has one sprue, one runner, and one ingate. The ingate cross-sectional area is 22.5 cm², the runner area is 18 cm², and the sprue area is 27 cm². Blind risers are placed at the ingate to act as slag traps, and open risers are placed on the upper surface of the axle housing. Internal chills are placed in the cavity, and external chills are placed at thick sections. This process achieves directional solidification and eliminates shrinkage defects.
I validated the optimized process through physical experiments. First, I conducted sectioning inspections. From the first two batches, two castings were sectioned every 10 cm. For five production batches totaling 630 axle housings, two castings per hundred were randomly selected and sectioned, resulting in 31 sectioned castings. No visible cracks or pores larger than 3 mm were found. This confirmed the internal quality improvement.
Second, I performed air tightness tests. The axle housing was sealed with tooling, submerged in water, and pressurized to 0.5 MPa for at least 10 minutes. Any bubble formation would indicate leakage. The test results for 20 samples from two batches are shown below.
| Sample Number | Test Pressure (MPa) | Sealing Condition | Test Time (min) | Leakage | Qualified |
|---|---|---|---|---|---|
| A1 | 0.5 | Good | 10 | No | Yes |
| A2 | 0.5 | Good | 10 | No | Yes |
| A3 | 0.5 | Good | 10 | No | Yes |
| A4 | 0.5 | Good | 10 | No | Yes |
| A5 | 0.5 | Good | 10 | No | Yes |
| A6 | 0.5 | Good | 10 | No | Yes |
| A7 | 0.5 | Good | 10 | No | Yes |
| A8 | 0.5 | Good | 10 | No | Yes |
| B1 | 0.5 | Good | 10 | No | Yes |
| B2 | 0.5 | Good | 10 | No | Yes |
| B3 | 0.5 | Good | 10 | No | Yes |
| B4 | 0.5 | Good | 10 | No | Yes |
| B5 | 0.5 | Good | 10 | No | Yes |
| B6 | 0.5 | Good | 10 | No | Yes |
| B7 | 0.5 | Good | 10 | No | Yes |
| B8 | 0.5 | Good | 10 | No | Yes |
| B9 | 0.5 | Good | 10 | No | Yes |
| B10 | 0.5 | Good | 10 | No | Yes |
| B11 | 0.5 | Good | 10 | No | Yes |
| B12 | 0.5 | Good | 10 | No | Yes |
All tested samples passed the air tightness test. By the end of the production period, more than 6,000 axle housings had been produced, with only 174 unqualified pieces, corresponding to a failure rate below 3%. This is a dramatic improvement from the original 70% defect rate. The optimized sand mold casting process has therefore been proven effective in reducing shrinkage porosity and shrinkage cavity defects, improving air tightness, and lowering production costs.
In conclusion, I designed and optimized a sand mold casting process for a divided tractor axle housing. The key findings are as follows. First, the semi-closed gating system with an area ratio of 1:0.8:1.2 provided the most stable filling and the best slag retention. Second, the pouring temperature of 1580 °C and pouring time of 10 s ensured complete filling and reduced thermal stress. Third, the addition of risers and chills promoted directional solidification and eliminated shrinkage defects. Fourth, the optimized process reduced the defect rate from 70% to below 3%, significantly improving product quality and reducing economic losses. The numerical simulation results agreed well with the experimental validation, demonstrating the reliability of the Procast-based optimization approach for sand mold casting of complex steel components.
For future work, I recommend further studies on the coupled simulation of flow, temperature, and stress fields to improve prediction accuracy. Additionally, measuring the actual thermophysical properties of the specific ZG40Mn alloy and the water-glass sand mold would reduce reliance on database values and further enhance simulation fidelity. The application of artificial intelligence and microstructural simulation could also provide deeper insights into the solidification behavior and mechanical properties of the axle housing. These advances would continue to improve the quality and efficiency of sand mold casting for heavy-duty tractor components.