Udemy – Design Optimization in CFD Using OpenFOAM

This course is a hands-on introduction to CFD-based design optimization using OpenFOAM, created to help learners move beyond flow visualization and into systematic, simulation-driven design improvement. The focus is on understanding how optimization problems are set up in CFD and why each configuration choice matters, rather than on solving large-scale industrial problems.

The course is intentionally built for learners who do not need prior knowledge of adjoint methods. All optimization concepts are introduced from a design and engineering perspective first, making it clear what is being optimized and how CFD can guide better designs. Mathematical complexity is kept to a minimum, while practical implementation details are emphasized throughout.

All example cases used in this course are simple and intentionally low-dimensional, developed solely for demonstrating the optimization workflow and solver setup. This ensures that learners can focus on understanding the methodology rather than dealing with complex geometries or large computational costs. For sensitivity analysis and shape optimization, a 2D flow past a square cylinder is used as the primary example. This canonical problem allows clear visualization of sensitivities, objective-function behavior, and boundary deformation while keeping the physics and mesh handling straightforward.

For topology optimization, a 3D internal flow problem with one inlet and two outlets is considered. In this case, the flow domain is optimized using a porosity-based approach, allowing material to be added or removed within the domain to guide the flow efficiently toward the outlets. The geometry and flow conditions are deliberately simplified so that the evolution of topology and porosity can be easily interpreted and visualized.

The course uses OpenFOAM v2412, and all demonstrations, case files, and dictionaries are fully compatible with this version. You will work directly with OpenFOAM solvers, optimization dictionaries, and post-processing tools, learning how to configure sensitivity analysis, shape optimization, and topology optimization in a consistent and reproducible way.

Special attention is given to common implementation pitfalls, such as missing source-term coupling in porosity-based optimization, improper constraint definitions, and unstable optimization behavior. Rather than hiding these issues, the course explains why they occur and how to fix them, helping you build confidence in diagnosing real optimization problems.

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