Common Simplifications in FEA Simulations for Enhanced Efficiency and Accuracy

Finite Element Analysis (FEA) is a crucial tool for engineers to simulate and analyze complex systems and structures without the need for extensive physical testing. However, to ensure that these simulations are efficient and accurate, several common simplifications are often applied. In this article, we will discuss various simplifications that can be made during an FEA simulation, along with practical examples and their benefits.

Linear Behavior and Material Models

The first simplification often made in FEA simulations is the assumption of linear behavior, which includes applications of Hooke's Law in mechanics, Ohm's Law in electricity, and Fourier's Law in heat transfer. These laws provide a straightforward and efficient way to model the behavior of materials under static loads and conditions. While linear behavior is a simplification, it is particularly useful in situations where the material does not exhibit nonlinear behavior under the applied loads. Hooke's Law, for instance, describes the linear relationship between stress and strain in elastic materials, making it a powerful tool for simplifying mechanical modeling.

Small Displacements and Rotations

Another common simplification is the assumption of small displacements and rotations in mechanical and structural analyses. This simplification is based on the fact that nonlinear effects are generally negligible when the displacements and rotations are small. For example, in structural mechanics, small rotations can often be added to the analysis without significantly compromising accuracy. This simplification is particularly useful in scenarios where large deformations are not expected, such as in civil engineering projects like bridge design.

Exploiting Symmetry and 2D Assumptions

With the increasing computational power available today, the use of symmetry to simplify 3D problems is becoming less common. However, exploiting symmetry remains a powerful tool in FEA simulations. By taking advantage of symmetry, engineers can reduce the complexity of the model and the computational resources required for analysis. For instance, when analyzing a symmetric part, only a quarter or half of the part needs to be modeled, achieving significant computational savings. Another simplification involves using plane stress or plane strain assumptions to reduce 3D problems to 2D. This approach is particularly useful in scenarios where the out-of-plane deformation is negligible, such as in thin-walled structures.

Concentrated Loads and Heat Sources

Concentrated loads and heat sources are often simplified to point sources or isolated discrete points. This simplification allows for a more focused and manageable model, especially when the distribution of loads or heat sources across the structure is not critical. For example, in structural analysis, a bolt or rivet can be treated as a point load, and in thermal analysis, a small resistor can be treated as a point heat source. This approach ensures that the computational resources are used efficiently, and the results are still accurate.

Extreme Conditions and Multi-Point Constraints (MPC)

Extreme conditions in elasticity, such as plane strain and plane stress assumptions, are used to reduce the complexity of 3D problems to 2D problems. Plane strain is used when out-of-plane deformation is negligible, such as in thin-walled structures, while plane stress is used when remote stress can be considered constant. Using these assumptions simplifies the analysis and makes it more manageable.

Modeling Parts as Rigid Bodies

For parts that are significantly stiffer than others, simplifying them as rigid bodies can further reduce the complexity of the model. This simplification is particularly useful in multibody dynamics analysis, where the interaction between rigid bodies is of primary interest. By modeling parts as rigid, the focus is shifted from individual deformations to the overall motion and interaction between the different components.

Material and Boundary Conditions

Assuming linear material, geometric, and boundary conditions is another common simplification. This means that the material properties, geometry, and boundary conditions are considered constant and linear. By making this assumption, the analysis becomes more straightforward and computationally less demanding. However, it is important to validate the assumption based on the actual conditions and material properties of the system.

Using Boundary Conditions Instead of Modeling Contact

In cases where modeling the interaction between different parts is complex or unnecessary, using boundary conditions can be a more efficient approach. By applying boundary conditions such as tie constraints or Dirichlet and Neumann conditions, engineers can effectively simulate the behavior of parts in contact without the need for detailed contact modeling. This simplification is particularly useful in scenarios where the contact behavior is not critical to the overall analysis.

Geometry Simplification and Defeaturing

Another common simplification in FEA is the defeaturing of parts, which involves removing small details and unnecessary features that do not significantly affect the analysis. For instance, fillets, small holes, and other minor details can often be omitted without affecting the overall results. This simplification is particularly useful in long and complex models where the accuracy of the analysis is not compromised by the removal of these features.

Modeling Less Important Parts as Point Masses and Omitting Gravity

For parts that have a minor effect on the overall behavior of the system, modeling them as point masses can be a practical simplification. Similarly, in transient analyses, gravity can often be omitted if it has a negligible effect on the results. These simplifications reduce the computational burden and make the simulation more manageable without sacrificing significant accuracy.

Simplified Material Models

Using simplified material models, such as linear elastic materials, can further reduce the complexity of the analysis. These models provide a straightforward way to represent the material behavior without the need for detailed nonlinear constitutive relationships. While this simplification reduces computational demand, it is important to ensure that the chosen material model accurately represents the material's behavior under the specific conditions of the analysis.

Ignoring Dynamic Inertia Effects and Performing Static FEA

When dynamic inertia effects are not critical to the analysis, performing static FEA can significantly reduce computational costs and improve efficiency. Static FEA provides accurate results for static loading conditions, which are often sufficient for preliminary or simplified designs.

Ignoring or Simplifying Joints

Joints such as welds and bolts can be simplified to reduce the complexity of the model. For example, tie constraints can be used to simulate welded joints, and bolts can be modeled as point contacts or simplified spring models. These simplifications help in managing the model size and computational resources while still maintaining acceptable accuracy.

Conclusion

In conclusion, simplifications play a crucial role in enhancing the efficiency and accuracy of FEA simulations. By applying these simplifications, engineers can achieve more manageable and computationally efficient models without significantly compromising the accuracy of the results. Understanding and utilizing these simplifications effectively is key to successful FEA analysis in engineering projects.