Yes, “real world” fluid flow problems are inherently complicated. Here are some factors that contribute to the difficulty of performing CFD:

1. Problem Understanding: One of the initial challenges in CFD is accurately defining and understanding the fluid flow problem at hand. This includes identifying the appropriate boundary conditions, understanding the flow physics, and selecting the relevant fluid properties. A clear understanding of the problem is essential for setting up the CFD simulation correctly.

2. Mesh Generation: Generating a suitable mesh is crucial for accurate CFD results. The mesh should adequately resolve the flow features and boundary layers while being efficient in terms of computational resources. Meshing complex geometries, handling moving boundaries, and ensuring adequate mesh quality can be challenging and time-consuming.

3. Turbulence Modeling: Turbulence is prevalent in many fluid flow situations, and modeling it accurately is crucial for CFD simulations. Selecting the appropriate turbulence model, setting relevant turbulence parameters, and understanding the limitations of the chosen model can be challenging. It requires an understanding of fluid dynamics and experience in selecting the most suitable turbulence model for the specific flow conditions.

4. Solver Settings and Convergence: Configuring the solver settings correctly is crucial to obtain reliable and accurate CFD results. This includes choosing the appropriate numerical schemes, convergence criteria, and time steps. Convergence can be a challenge, especially for complex flow problems and transient simulations. Properly configuring the solver and iteratively refining the analysis settings may be required.

5. Post-processing and Interpretation: Analyzing and interpreting CFD results require expertise and experience. Visualizing and extracting meaningful information from large datasets, interpreting flow patterns, identifying regions of interest, and relating the results to engineering design and performance goals can be challenging. Care must be taken to ensure the results are validated and used appropriately.

6. Computational Resources: CFD simulations can be computationally demanding, requiring significant computational resources in terms of memory, processing power, and storage. Handling large meshes and long simulation times can be challenging, particularly with limited resources. Proper resource allocation and optimization strategies are necessary to efficiently perform CFD simulations.

7. Experimental Validation: Validating CFD results against experimental data is essential to establish confidence in the simulations. Designing and conducting appropriate experiments, acquiring accurate measurements, and comparing the experimental and numerical results can be challenging. It requires expertise in experimental techniques and data analysis.