I have the following problem for which an experimental design has to be created:

The stress at a certain point of a model is to be determined by FEA. This model is varied by setting three different parameters. These parameters are to be varied in such a way that the stress is minimized. The stress should be the target value. Angle, modulus and radius are the factors whose influence must be investigated.

Now comes the more complex part of defining the factors and levels:

Angle: 3 levels for different angles

Module: 9 different modules

Radius: for each combination of angle and module there is a different lower and upper limit between which each value can be assumed

My question now is how best to deal with the dependency of the radius? Should the radius simply be normalized between 0 and 1 in the doe and then converted when the radius is used in the experiment?

Would you assume discrete numerical factors oder categorical factors for angle and modulus in this case... that still confuses me.

According to my research so far, a D optimal design would be best to collect the data and then RSM to find the optimal parameter combination for the optimality criterion?

Are there better ways to solve the problem?

Thank you so much.