Data-driven surrogates are the most popular replacement models utilized in many fields of engineering and science, including design of microwave and antenna structures. The primary practical issue is a curse of dimensionality, which limits the number of independent parameters that can be accounted for in the modeling process. Recently, a performance-driven modeling technique has been proposed where the constrained domain of the model is spanned by a set of reference designs optimized with respect to selected figures of interest. This approach allows for significant improvement of prediction power of the surrogates without the necessity of reducing the parameter ranges. Yet uniform allocation of the training data samples in the constrained domain remains a problem. Here, a novel design of experiments technique ensuring better sample uniformity is proposed. Our approach involves uniform sampling on the domain-spanning manifold and linear transformation of the remaining sample vector components onto orthogonal directions with respect to the manifold. Two antenna examples are provided to demonstrate the advantages of the technique, including application case studies (antenna optimization).
|Journal||International Journal of Numerical Modelling: Electronic Networks, Devices and Fields|
|Publication status||Published - Sept 2019|
Bibliographical noteFunding Information:
The authors would like to thank Dassault Systemes, France, for making CST Microwave Studio available. This work is partially supported by the Icelandic Centre for Research (RANNIS) grant 174114051 and by the National Science Centre of Poland (Narodowe Centrum Nauki) grants 2015/17/B/ST6/01857, 2011/03/B/ST7/03547, and 2016/23/B/ST7/03733.
© 2019 John Wiley & Sons, Ltd.
- antenna design
- constrained modeling
- data-driven modeling
- design of experiments
- simulation-based design
- uniform sampling