Hello,
I have a few questions and will appreciate thoughts on it.

For the adaptive technique, how do you select the initial experimental design for a given problem. Is there a rule of thumb or reference you could point me to? For example, if my limit state function has only three variables  what might be the number of initial sample points before enrichment?

In terms of the Kmeans clustering approach, how do one determine the number of clusters  is this user defined or is there a means of determining the number of clusters for multiple enrichment of experimental design? In other words, how to determine K (any rule of thumb or user defined)

Also, is the active learning method quite time consuming due to the size of the candidate sample pool especially for problems with small failure probability?

If using a PCKriging metamodel does it take a larger training time compared to ordinary Kriging? Any advantage of PCK over ordinary Kriging in terms of training time and result accuracy?

How do we handle input dependent variable during PCK training?
Appreciate thoughts on this