Documentary Report on Optimization of Sand Casting Molds Based on SolidWorks Fluid and Thermodynamic Analysis

Core Technologies: SolidWorks Flow Simulation (Fluid Module), SolidWorks Simulation (Thermodynamic Module)

Application Scenario: Design and Manufacturing of Sand Molds for QT450-10 Ductile Iron Machine Tool Beds via Sand Casting

1. Introduction: Core Pain Points and Technical Requirements in Sand Mold Manufacturing for Sand Casting

As a manufacturer specializing in heavy-duty machine tool castings, our factory has long faced the problem of mismatch between mold design and molten metal fluidity before 2025. When designing molds using the traditional "empirical trial mold method", unreasonable gating and riser layout, uneven heat dissipation of sand molds, and excessive runner resistance often led to casting defects such as cold shuts (defect rate: 12.8%), shrinkage cavities (defect rate: 9.5%), and gas pores (defect rate: 7.2%). In 2024 alone, the waste loss caused by mold design reached 1.86 million yuan, and the trial mold cycle was as long as 2-3 weeks, seriously affecting order delivery efficiency.

To solve the above problems, the Technology Department introduced the SolidWorks Fluid and Thermodynamic Modules in January 2025, and carried out simulation optimization focusing on the coupling relationship among "mold structure - molten metal flow - temperature field change". The core objectives are: to predict the flow trajectory of molten metal and temperature attenuation law through digital simulation, optimize the mold structure design, reduce the core defect rate of castings to below 5%, and shorten the trial mold cycle to within 1 week.

2. SolidWorks Technical Solution: Collaborative Application of Fluid and Thermodynamic Modules

2.1 Preliminary Modeling: Restoring the Real Scenario of Mold and Gating System

First, based on the 3D drawings of the machine tool bed casting (size: 2800mm×1200mm×600mm, single weight: 3.2t) in our factory, 1:1 3D modeling of mold body, sprue, runner, ingate, riser, and vent hole was completed in the SolidWorks Part Module. The key parameters are as follows:

· Mold Material: Resin-bonded sand (thermal conductivity: 0.32W/(m·K), specific heat capacity: 1100J/(kg·K));

· Molten Metal: QT450-10 ductile iron (pouring temperature: 1380℃, liquid density: 6800kg/m³, liquid viscosity: 0.006Pa·s, solidification temperature range: 1150-1200℃);

· Gating System: Bottom gating + side riser (initial sprue diameter: 80mm, runner cross-sectional area: 6000mm², number of ingates: 4).

During the modeling process, special attention was paid to the gap between the sand mold and the casting (3-5mm coating layer) and the distribution of vent holes (interval: 200mm, diameter: 10mm) to ensure that the model is completely consistent with the actual production scenario.

2.2 Fluid Module (Flow Simulation): Optimizing the Flow Characteristics of Molten Metal

2.2.1 Simulation Parameter Setting

The 3D mold model was imported into the SolidWorks Flow Simulation Module, and the "molten metal flow" analysis type was selected. The core parameters were set as follows:

· Boundary Conditions: The sprue inlet was set as "mass flow boundary" (according to the actual pouring speed of 1.2kg/s), the inner wall of the mold was "no-slip wall", and the vent hole was "atmospheric pressure boundary";

· Physical Model: "Non-Newtonian fluid" was enabled (since the viscosity of ductile iron melt changes significantly with temperature), and "gravity effect" was enabled (vertical direction: -9.81m/s²);

· Mesh Generation: "Fine mesh" (mesh size: 5mm) was used for key areas such as runners and risers, and "coarse mesh" (mesh size: 20mm) was used for the outer wall of the mold. The total number of meshes was about 1.2 million to balance calculation accuracy and efficiency.

2.2.2 Simulation Results and Structural Optimization

Two major problems were found in the first simulation:

1. Uneven Flow Rate of Ingate: The flow rate of Ingate 1# and 2# near the sprue reached 1.8m/s (excessively fast, easy to entrain gas), while the flow rate of Ingate 3# and 4# far from the sprue was only 0.6m/s (excessively slow, easy to form cold shuts);

0. Flow Dead Zone: There was a flow stagnation zone at the corner (R50mm) of the bed casting, and the filling time of molten metal exceeded 8s (exceeding the critical solidification time of 6s), which was prone to shrinkage porosity.

To solve the above problems, the Technology Department iteratively adjusted the mold structure through the "parameter optimization analysis" function of the SW Fluid Module:

· The cross-sectional area of the ingate was changed from "uniform 6000mm²" to "gradient design" (cross-sectional area of Ingate 1# and 2#: 5000mm², cross-sectional area of Ingate 3# and 4#: 7000mm²) to balance the flow rate of each ingate;

· The sand mold at the corner of the casting was changed to "diversion fillet" (R80mm), and an auxiliary ingate (diameter: 50mm) was added to eliminate the flow dead zone.

The second simulation after optimization showed that: the flow rate of each ingate was stably maintained at 1.1-1.3m/s, the overall filling time of the casting was shortened to 5.2s, the flow uniformity was improved by 42%, and there were no obvious gas entrainment and stagnation zones.

2.3 Thermodynamic Module (Simulation): Controlling the Temperature Field and Solidification Process

2.3.1 Simulation Model Construction

The mold model optimized by the fluid module was imported into the SolidWorks Simulation Module, the "transient thermal analysis" type was selected, and a heat conduction model of "mold - molten metal - environment" was established. The key settings are as follows:

· Thermal Properties of Materials: The thermal conductivity of ductile iron was set in sections (liquid state: 18W/(m·K), solid state: 35W/(m·K)), and the heat dissipation coefficient of the sand mold (surface heat dissipation coefficient: 15W/(m²·K)) was set;

· Initial Conditions: The initial temperature of molten metal was 1380℃, and the initial temperature of the mold was 25℃ (room temperature);

· Analysis Duration: 3600s (1 hour) was set to cover the entire cycle of "filling - solidification - cooling".

2.3.2 Simulation Results and Structural Optimization

Two major problems were found in the first thermal simulation:

1. Insufficient Riser Feeding: The time for the temperature of the central area of the casting (thickness: 60mm) to drop to 1150℃ (solidification temperature) was 850s, while the time for the temperature of the riser center to drop to 1150℃ was only 720s. The "premature solidification" of the riser led to the failure of feeding and the generation of shrinkage cavities;

0. Uneven Heat Dissipation of Mold: The heat dissipation in the contact area between the mold bottom and the ground was too fast (temperature drop rate: 250℃/h), leading to the first solidification of the casting bottom and the formation of "temperature difference stress" with the upper molten metal, which was prone to cracks.

To solve the above problems, combined with the "temperature field cloud map analysis" function of the SW Thermodynamic Module, the mold design was optimized:

· Increase the riser size: The riser diameter was increased from 150mm to 180mm, and the height was increased from 200mm to 250mm, extending the riser solidification time to 950s to ensure "riser solidifies after the casting";

· Add thermal insulation layer at the mold bottom: A 50mm-thick ceramic thermal insulation cotton (thermal conductivity: 0.08W/(m·K)) was laid at the mold bottom to reduce the bottom heat dissipation rate to 120℃/h.

The thermal simulation after optimization showed that: the solidification time difference between the casting center and the riser reached 230s, and the feeding effect was significant; the overall temperature gradient of the mold was reduced from 35℃/100mm to 18℃/100mm, and the temperature difference stress was reduced by 54%.

2.4 Coupling Verification: Fluid-Thermodynamic Collaborative Simulation

Considering the interaction between molten metal flow and temperature change (flow accelerates heat conduction, and temperature decrease increases melt viscosity), the Technology Department used the "multi-physics coupling" function of SW to take the "flow velocity field data" of fluid analysis as the "forced convection boundary condition" of thermodynamic analysis for coupling simulation.

The results showed that: the casting solidification time of the coupled simulation (880s) was closer to the actual production (measured 890s) than that of the single thermal simulation (850s), and the error was reduced from 3.5% to 1.1%, which verified the accuracy of the optimization scheme.

3. Practical Effect Verification: Mold Manufacturing and Casting Quality Improvement

3.1 Mold Manufacturing Implementation

According to the 3D drawings optimized by SW simulation, the casting workshop of our factory completed the mold production: the resin-bonded sand automatic molding line was used to make the sand mold, and the gradient size of the ingate, the riser accuracy (error ≤ ±2mm), and the laying thickness of the thermal insulation layer were strictly controlled. The first trial mold only took 5 days (shortened by 58% compared with the traditional cycle).

3.2 Casting Quality Inspection

From March to June 2025, our factory produced 120 pieces of QT450-10 machine tool bed castings using the optimized mold, and verified the quality through "appearance inspection + non-destructive testing (UT/MT) + mechanical property testing":

Among them, 3 castings were sent to a third-party testing institution (National Foundry Product Quality Supervision and Inspection Center) for testing, and the internal quality grade reached Grade 2 in GB/T 7233.1-2019 "Steel Castings - Ultrasonic Testing - Part 1: General Requirements" (Grade 4 before optimization), which fully meets the high-precision requirements of customers for heavy-duty machine tool beds.

3.3 Economic Benefit Calculation

By June 2025, the optimization scheme had reduced 11 waste castings, saving about 352,000 yuan in raw material costs; the shortened trial mold cycle reduced the equipment standby loss by 286,000 yuan; the improved order delivery efficiency brought 3 new orders (contract amount: 4.5 million yuan), with comprehensive economic benefits exceeding 5 million yuan.

4. Conclusions and Prospects

1. Technical Conclusions: The SolidWorks Fluid Module can accurately predict the flow trajectory of molten metal, and balance the flow rate by optimizing the gating layout and size; the Thermodynamic Module can effectively control the temperature field and improve the feeding effect by adjusting the riser and thermal insulation measures. The collaboration of the two modules can reduce the core defect rate of sand castings to below 5%.

0. Future Plans: In the next step, the "topology optimization" function of SolidWorks will be introduced to reduce the mold weight while ensuring strength; and a "fluid-thermodynamic" simulation database will be established based on production data to further shorten the mold design cycle for new products.