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A comparison of techniques for finding coefficients of polynomial chaos models for antenna problems
Author(s) -
Klink Dieter,
Meyer Petrie
Publication year - 2021
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/mmce.22729
Subject(s) - monte carlo method , polynomial chaos , range (aeronautics) , mathematics , computer science , algorithm , basis (linear algebra) , mathematical optimization , polynomial , statistical physics , mathematical analysis , geometry , statistics , physics , engineering , aerospace engineering
Abstract A range of different techniques for determining the unknown coefficients of Polynomial Chaos Expansion (PCE) models for antenna structures, are presented. PCE models offer significant advantages over Monte Carlo analysis, for the modeling of the statistical behavior of structures, but the different approaches for calculating the PCE model coefficients exhibits a large variation in the number of required basis points, that number also being problem specific. A range of model coefficient calculation techniques are evaluated in this article, for the problem of modeling cross‐polarization of an inset‐fed patch antenna. This structure is one of the most widely used antenna structures, often produced in high‐volume, and serves as an excellent example to emphasize the variation in performance between the different techniques, and problem‐specific nature of finding an optimal solution. It is shown that the most optimal method requires fewer than 10% analysis points of the least optimal, and a factor of 100 fewer points than Monte‐Carlo analysis.