Yes , FEA problems can be very difficult. The level of difficulty can vary depending on several factors, including the complexity of the problem, the level of accuracy required, the software used, and the engineer's experience and knowledge in FEA.
Here are some factors that can contribute to the difficulty of performing FEA:
1. Problem Understanding: One of the initial challenges in FEA is correctly defining and understanding the problem at hand. This includes identifying the appropriate boundary conditions, material properties, and load cases, as well as selecting the suitable element types and meshing strategies. It requires a good grasp of engineering principles and a clear understanding of the physical behavior of the system being analyzed.
2. Mesh Generation: Creating an appropriate mesh is critical for accurate results. Generating a mesh that adequately represents the geometry, captures the important features, and provides sufficient resolution can be challenging, especially for complex geometries. The engineer needs to balance computational efficiency with accuracy and ensure that the mesh is refined in areas of interest.
3. Material Modeling: Accurately representing the behavior of materials is essential in FEA. Choosing appropriate material models, assigning accurate material properties, and considering non-linear or time-dependent behavior can add complexity to the analysis. It requires a good understanding of material science and the limitations of the chosen material models.
4. Solver Settings and Convergence: Configuring the solver settings correctly is crucial to obtain accurate and reliable results. This includes selecting appropriate solution techniques, convergence criteria, and numerical parameters. Iterating and refining the analysis settings may be required to achieve convergence, especially for non-linear problems.
5. Interpreting and Validating Results: Analyzing and interpreting the results of FEA requires technical expertise and experience. Understanding stress and strain distributions, identifying areas of concern, and assessing the validity of the results against engineering standards or experimental data can be challenging. Care must be taken to avoid misinterpretation or overreliance on the results.
6. Time and Computational Resources: FEA can be computationally demanding, especially for large and complex models. The analysis may require significant computational resources, such as memory and processing power. Optimizing the analysis setup and balancing accuracy with computational efficiency can be a challenge, particularly when dealing with limited resources.