An accumulative error based adaptive design of experiments for offline metamodeling

Abstract

A popular method to reduce the computational effort in simulation-based engineering design is by way of approximation. An approximation method involves two steps: Design of Experiments (DOE) and metamodeling. In this paper, a new DOE approach is introduced. The proposed approach is adaptive and samples more design points in regions where the simulation response is expected to be highly nonlinear and multi-modal. Numerical and engineering examples are used to demonstrate the applicability of the proposed DOE approach. The results from these examples show that for the same number of simulation evaluations and according to metamodel accuracy, the proposed DOE approach performs better for majority of test examples compared to two previous methods, i.e., the maximum entropy design method and maximum scaled distance method.