Model Validation and Error Modeling to Support Sequential Sampling
Yao Lin, Dong Luo, Trevor Bailey, Ritesh A. Khire, Jiachuan Wang, Timothy W. Simpson · 2008
Several model validation and prediction error modeling techniques are studied and compared in this paper to help establish stopping criteria and identify critical regions in the design space in a sequential sampling framework. This study leads to the proposal of a two-phase sequential sampling and meta-modeling strategy, which is realized by the support of a multi-dimensional data visualization tool. These techniques have been successfully applied in the development and setup of a system-level parametric tool to support Heating, Ventilating, and Air Conditioning design. Maintaining the same level of accuracy, we observe a savings of 6–30 times the simulation effort needed for current practice. The benefits and drawbacks of the method are discussed, and opportunities are identified for future improvement.