Petrie Meyer

The operation of microwave components can be severely degraded by manufacturing tolerances. Yield-driven optimization delivers a systematic approach to mitigating manufacturing-induced uncertainties but is often computationally burdensome due to the large number of full-wave electromagnetic (EM) simulations required. The computational cost is commonly reduced with the use of Surrogate-based techniques; however, these techniques are limited when applied in isolation to high-dimensional uncertainty spaces. This work proposes a feature-based non-linear partial least squares polynomial chaos expansion (NLPLS-PCE) approach that simultaneously reduces response complexity through performance-relevant feature modeling and input dimensionality through latent-variable representation, thereby mitigating the curse of dimensionality. Feature-based NLPLS-PCE is incorporated within a swarm intelligence framework for adaptive adjustment of design variables and convergence safeguard. The yield optimization method is demonstrated using a Ka-band ridge waveguide filter terminated with a Vivaldi antenna. The reliability and performance of the yield optimization algorithm are verified through EM-driven Monte Carlo (MC) simulations.

This paper presents the design of a ridge gap waveguide filter with vertically aligned resonators, utilizing both vertical and longitudinal coupling to create transmission zeros on the upper sideband of the filter. The vertically stacked configuration allows for an array of filters to fit underneath a slotted waveguide antenna array. The designed 7th order filter with a 5 GHz bandwidth centered at 100 GHz implements two transmission zeros at 103.2 and 107.6 GHz achieves a maximum return loss in the passband of 15 dB with PEC metals.

We propose and evaluate contractual- and Intellectual Property (IP) instruments in support of research collaboration partnerships between universities and the Small, Medium and Micro Enterprises (SMME)-industry, and more specifically in the South African context. Interviews were conducted with executives from 11 South African originated SMME’s in the high-technology industry. The findings of this study and potential solutions were then verified and validated with SMME’s, large multinational industry and universities (in South Africa and international) and can be considered as good practice principles to assist in industry-university collaboration (IUC). One aspect that was reported with high occurrence, is the matter of IP valuation, as it can often create further barriers in IUC. The question regarding how to value the IP and any rights relating thereto (IPR’s), is attended to in this study and shared experiences from industry and universities provide insights in the considerations and principles to be used when entering discussions regarding IP valuation.

In this paper, a resonator and second order filter are fabricated using a novel technological process based on micromachining and thermo-diffusion. The use of this innovative process opens the way to the design of RF components relying on partially air-filled Substrate Integrated Waveguides (SIW). These topologies and particularly the proposed partially air-filled pedestal SIW resonator is suitable to design high-Q, yet compact SIW resonators. In this paper, a study of partially air-filled pedestal SIW resonator is proposed to offer an optimized trade-off between Q-factor and compactness. Then, based on this study, a partially air-filled pedestal resonator working at 5 GHz is designed and manufactured. The measured prototype exhibits a Q-factor of 285, which represents a 53 % increase in Q-factor compared to a fully dielectrically-filled-in pedestal SIW resonator, while the size is kept constant. Finally, a second order filter based on this resonator topology is also designed, measured and discussed.

This paper presents a Non-Linear Partial-Least-Squares-based Polynomial Chaos Expansion (NLPLS-based PCE) approach for high dimensional global sensitivity analysis. NLPLS-based PCE effectively reduces the system dimensionality using NLPLS and simultaneously extracts the statistical information on the same sample set, i.e. variance, using PCE. A post-processing step is applied to transform the NLPLS-based PCE surrogate to a standard PCE surrogate, described by the full set of system parameters. A variance-based global sensitivity analysis is then applied, quantifying each system parameter’s sensitivity as the partial influence on the total variance of the performance variable. This method is illustrated using a high-dimensional problem, namely, a 37-variable passive diplexer structure, requiring 30 analysis points to obtain a converged global sensitivity analysis. The diplexer is optimized for manufacturing and the fabricated diplexer performs as expected. Another 37-variable global sensitivity analysis is performed and compared to the original diplexer.

A VHF/UHF band notch filter with helical resonators is developed to provide a deep notch with low loss in the pass-band of the filter. The traditional implementation of helical resonators is slightly altered to enable tuning opportunities in future designs. The helical resonators are coupled together using a non-standard coupling technique in order to provide a stopband response. The measured results show a notch depth of -81 dB at 260 MHz with the loss in the pass-band of -0.4 dB.

For high-volume manufacturing, yield estimation is an important design step to determine the effects of uncertainties in the fabrication process. The tolerances associated with the fabrication process are applied to the statistically significant system parameters, and a Monte Carlo (MC) simulation is historically done to accurately estimate the yield. This process becomes computationally very expensive when the number of statistically significant system parameters are either too difficult to intuitively determine or are too high. A nonlinear partial-least-squares-based polynomial chaos expansion (NLPLSs-based PCE) is proposed as a solution for complex antenna yield analysis. NLPLS-based PCE effectively reduces the system dimensionality using NLPLS and simultaneously extracts the statistical information on the same sample set, that is, yield, using PCE. It is also possible to perform a global sensitivity analysis using NLPLS-based PCE surrogates, providing an additional advantage. This method is illustrated using an eight-variable single-frequency patch antenna, an eight-variable dual-band patch antenna, and a 37-variable diplexer requiring 30, 10, and 30 analysis points, respectively, to obtain converged yield estimates.

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.