Sequential experimental designs for nonlinear regression metamodels in simulation

The construction of a nonlinear regression metamodel for simulation requires experimental designs that better explore the nonlinearities of the system. The proposed sequential procedure focuses on simulation scenarios in sub-regions where the input–output behavior is more interesting. It takes into account, not only the inputs, but also the output (response) value of the metamodel. The resulting experimental design ensures that the scaled response values are evenly spread over a scaled response surface. Although the focus is on nonlinear regression metamodels, the method may be applied to other types of metamodels. This design procedure is illustrated for one-dimensional and two-dimensional inputs, and the results are compared with space filling designs. The use of bootstrapping for metamodel validation stresses the importance of validation in a metamodeling context.