Surrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge. Notwithstanding, a typically high nonlinearity of system outputs and the curse of dimensionality limit the applicability of conventional methods to relatively simple structures described by a few parameters within narrow ranges thereof. A recently reported nested kriging alleviates these difficulties from the perspective of an appropriate definition of the model domain. By focusing the modeling process on the region containing design that are optimized for the selected performance figures, it enables the construction of reliable surrogates over wide ranges of geometry/material parameters and operating conditions, both at a practically acceptable computational cost. The relative model domain thickness (i.e., its lateral-to-tangential size), determines the trade-off between the surrogate region of coverage and its predictive power, the former being essential for practical applications of the model, especially design optimization. This paper proposes a simple and computationally efficient procedure for automatic selection of the thickness parameter, which, in the original version of the method, was to be selected by the user. The importance of this aspect of the modeling process and the benefits of the proposed approach are demonstrated using a dual-band dipole antenna and miniaturized microstrip coupler.

替代模型正在成为减轻与电磁（EM）驱动的高频结构设计的过高成本有关的问题的首选工具。在可用的技术中，由于其通用性，近似建模是迄今为止最受欢迎的技术。特别地，替代物完全基于采样的模拟数据，而无需涉及工程学见识或特定于问题的知识。尽管如此，系统输出通常具有很高的非线性度和维数的诅咒将常规方法的适用性限制在由较窄范围内的几个参数所描述的相对简单的结构上。最近报道的嵌套克里金法从模型域的适当定义的角度减轻了这些困难。通过将建模过程集中于针对所选性能图进行了优化的包含设计的区域，它可以在几何/材料参数和操作条件的广泛范围内构造可靠的替代物，而这两者都是实用的计算成本。相对的模型域厚度（即其横向到切向大小）决定了覆盖的替代区域与其预测能力之间的平衡，前者对于模型的实际应用（尤其是设计优化）是必不可少的。本文提出了一种自动选择厚度参数的简单且计算效率高的程序，该方法在原始方法中由用户选择。