Thomas Dick

"Development of a gradient smoothing method for shape optimization in SU2"

For gradient based shape optimization the application of second order derivatives could greatly improve performance. Many possible ways to approximate a Hessian have been investigated in the past. In this talk we will discuss the Sobolev gradient method for incorporating second order derivative information. This talk will give an overview of the mathematical background and show a sequential quadratic programming method for this case. Furthermore, the implementation of this method into the existing shape optimization capabilities of the SU2 multiphysics and design software will be discussed.

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