Unleashing the Power of Linkage Rod Connectors: A SOLIDWORKS Simulation Case Study

Trash Dumping 4-bar Mechanism:
The lifting mechanism shown in the below image resembles a four-bar linkage system commonly used in dump trucks to control the tilting motion of the truck bed. In this mechanism, the truck chassis acts as the fixed link, the bed forms the output link, and the connecting arms serve as couplers to transfer motion. The hydraulic cylinder provides the input force, rotating the linkage to lift the bed at a controlled angle. This four-bar linkage design ensures smooth and stable lifting, allowing precise dumping of materials like soil, sand, or waste without sudden jerks. The mechanism’s practical advantage lies in its simplicity, durability, and ability to handle heavy loads, making it ideal for construction, agriculture, and waste management industries where efficient material handling is essential.

Four bar mechanism SOLIDWORKS Assembly

Traditional Approach: In a traditional simulation workflow, the connecting rods and other linkage components are modeled with their actual, detailed 3D geometry. This involves creating precise 3D CAD models of each part, including all complex features like holes, fillets, and varying cross-sections. When these detailed models are brought into SOLIDWORKS Simulation for analysis, the system generates a fine mesh to capture the intricate geometry accurately. However, this increases simulation time and requires more computational resources due to the higher number of elements in the mesh.

For example, when simulating the stress distribution and deformation of the four-bar linkage in a dump truck under a heavy load, the detailed model will result in a larger mesh and more complex calculations, which can slow down the analysis. While accurate, this approach may not always be the most efficient for early design validation.

Linkage Rod Connector Approach: Replace the physical rods with Linkage Rod Connectors. These connectors, available in SOLIDWORKS Simulation in Professional and premium license represent the rods as idealized beam elements. By defining the connector’s endpoints on the connected components and specifying its material properties (e.g., Young’s Modulus, a cross-sectional area matching the actual rod’s dimensions), you can accurately capture the axial force transfer while significantly simplifying the model and reducing mesh complexity. This leads to faster simulations with minimal impact on accuracy for applications where axial forces dominate.

Boundary conditions and loads:
Fixture is applied to the baseplate fixed to the vehicle and load is applied on the mounting plate of 300 lb.

Mesh details and solution time:

The solution time required for the actual link geometry is noticeably longer compared to that of the linkage rod connector. This difference can be attributed to the fact that the actual link geometry involves a much higher number of mesh elements. The increased mesh density in the actual link geometry leads to more complex computations, which in turn extends the overall solution time. In contrast, the linkage rod connector requires fewer mesh elements, resulting in faster computational performance.

Validation of Linkage Rod Connectors:
Position 1: Initial lift
Linkage Rod Connectors:

Model with linkage arm geometry:

Position 2: Holding vertical tilted to 90 degrees.
Linkage Rod Connectors:

Model with linkage arm geometry:

The simulation results provide valuable insights into the accuracy of Linkage Rod Connectors in SOLIDWORKS Simulation. By comparing the results obtained using Linkage Rod Connectors with those obtained from a model using the actual geometry of the connecting rods (as shown in the top images), we can observe how effectively the connectors represent the behavior of the physical components.

These comparisons demonstrate that, in many cases, Linkage Rod Connectors provide highly accurate results while significantly reducing computational resources and simulation time. By replacing complex 3D rod geometries with idealized beam elements, the model complexity is reduced, leading to faster simulations and improved efficiency. This approach is particularly beneficial for analyzing assemblies with numerous slender components, where the computational cost of using detailed 3D models can be substantial.

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