Abstract
A reliable design of contemporary antenna structures necessarily involves full-wave electromagnetic (EM) analysis which is the only tool capable of accounting, for example, for element coupling or the effects of connectors. As EM simulations tend to be CPU-intensive, surrogate modeling allows for relieving the computational overhead of design tasks that require numerous analyses, for example, parametric optimization or uncertainty quantification. Notwithstanding, conventional data-driven surrogates are not suitable for handling highly nonlinear antenna characteristics over multidimensional parameter spaces. This paper proposes a novel modeling approach that employs a recently introduced concept of domain confinement, as well as principal component analysis. In our approach, the modeling process is restricted to the region containing high-quality designs with respect to the performance figures of antennas under design, identified using a set of pre-optimized reference designs. The model domain is spanned by the selected principal components of the reference design set, which reduces both its volume and dimensionality. As a result, a reliable surrogate can be constructed over wide ranges of both operating conditions and antenna parameters, using small training datasets. Our technique is demonstrated using two antenna examples and is favorably compared to both conventional and constrained modeling approaches. Application case studies (antenna optimization) are also discussed.
Highlights
The design of contemporary antennas is a multifaceted process which requires handling of various performance figures and constraints that are pertinent to both electrical and field characteristics and account for interactions with environmental components [1,2]
High simulation cost is especially problematic for topologically complex structures that are being developed in order to meet stringent performance requirements and to realize various functionalities, such as multi-band operation [3], band notches [4], or circular polarization [5]
The first observation is that both performance-driven approaches are noticeably better than the conventional models, which indicates the importance of domain confinement
Summary
The design of contemporary antennas is a multifaceted process which requires handling of various performance figures and constraints that are pertinent to both electrical and field characteristics and account for interactions with environmental components (other radiators, housing, installation fixtures, human body, etc.) [1,2]. The originality and advantages of the presented methodology include the following: (i) simple implementation, (ii) a possibility of reducing the problem dimensionality by focusing on the parameter space directions that correspond to the highest variance of the reference designs, (iii) rigorous determination of the required domain dimensionality based on the analysis of the reference set eigenvalues, (iv) improved scalability of the surrogate model predictive power with respect to the training dataset size, (v) straightforward uniform sampling, and (vi) straightforward utilization of the surrogate for design purposes All of these are thoroughly investigated and demonstrated using two antenna structures for which accurate models are established with a small number of data points.
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