Adjoint Shape Optimization

An adjoint shape optimization uses adjoint sensitivities to derive an optimized shape with respect to the user-defined cost functions. For example, an optimized duct shape reduces the total pressure drop (cost function) in the duct.

The calculation of the sensitivity is based on the previously obtained adjoint solution:

  • When using mesh sensitivity, you compute new positions of control points by adding or subtracting a small fraction of the mesh sensitivity, the mesh can be deformed to increase or reduce the cost function , respectively.

    Refer to the tutorial Adjoint Shape Optimization: Mesh Sensitivity for Dual Element Wing for an application using mesh sensitivity.

  • When using the surface sensitivity, you compute new position of the surface using boundary displacements calculated by adding or subtracting a small fraction of the surface sensitivity.

    Refer to the tutorial Adjoint Shape Optimization: Surface Sensitivity for S-Bend for an application using surface sensitivity

To obtain an optimal solution within a certain range of the allowed displacement, you rerun the primal solutions with the previously optimized shape to visualize the improvement on cost function. Once the primal solution is converged, the adjoint can be solved again. The shape optimization cycle is repeatable as long as the geometrical design and mesh quality allow.