Smart Shape Optimization with the ANSYS Adjoint Solver
Imagine that you have to design a car and minimize its drag, or engineer a piping system and minimize pressure drop. In both cases, the actual shape of the design is the most important factor. When setting parameters for simulation, usually you define the shape and run parametric variations, often with the help of optimization tools. While this is a good approach, it has many limitations:
- Design shapes can be extremely complex, governed by hundreds of parameters (or more). It is impossible to consider all of them. How do you make sure that you select the relevant parameters?
- Even if you select one set of key design shape parameters, you still have a very large number of designs to evaluate. Simulating all these can be extremely time consuming.
For these reasons, you need a smart shape optimization tool — one that:
- Automatically identifies the section of the design (shape) that needs to be modified
- Automatically guides shape optimization by determining how to modify the shape directly from simulation results, without the need for trial-and-error simulation run after run
- Quickly performs design shape optimization with the minimum amount of simulations, and performing those simulations as fast as possible
What is the smart shape optimization tool?
The ANSYS smart shape optimization tool is called adjoint technology. The tool is actually a solver that uses CFD simulation results to find an optimal solution based on stated goals (reduced drag, maximized lift-over-draft ratio, reduced pressure drop, etc.). But it doesn’t stop there: It also computes how to specifically modify the design. Because it is a solver, it has many advantages:
- It directly computes which section of the design needs to be modified and how. You do not need to define any parameters.
- It directly determines a better-performing shape as well as the associated performance improvement, all without needing another CFD simulation.
- It can, in a minimal number of simulations, determine the optimal shape. At each iteration, design performance increases until the optimal design is reached.
Why is this smart shape optimization tool so fast?
Because the adjoint solver directly determines which section of the shape to modify and how to do it, it reaches the optimal geometry faster. Because the adjoint solver works hand-in-hand with mesh morphing technologies, you do not need to redefine the geometry nor recreate the computational mesh; rather you simply morph the mesh to the new shape. In summary, this solution is fast because:
- The adjoint solver determines directly how to improve performance, so there is no time wasted on trial-and-error processes.
- A mesh morpher automatically adjusts the design shape and computational mesh following the adjoint solver recommendations, saving even more time.