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Design closure exploiting electromagnetic (EM) solvers has become one of the fundamental design tools in contemporary microwave engineering. For many structures, adjustment of geometry and/or material parameters can only be done through repetitive EM simulations because analytical design formulas either do not exist or can only provide initial designs that need to be further refined. Unfortunately,...
A robust and computationally efficient technique for design optimization of microwave structures is proposed. We exploit co-simulation-based surrogate models with the essential couplings evaluated using EM solver and most of the designable parameters modelled by distributed circuit elements with physical dimensions corresponding to those of the structure being optimized. Good prediction capability...
A space mapping technique is presented that utilizes recent commercially available adjoint sensitivity analysis procedures for modeling microwave and RF components. It is shown that using only one full-wave electromagnetic simulation along with an adjoint sensitivity evaluation one can build a good surrogate model. The proposed technique calibrates a surrogate by matching responses and corresponding...
Coarse model is a critical component of the space mapping (SM) optimization algorithm. It should be fast and reasonably accurate. A popular choice of the coarse model is an equivalent circuit. Circuit models are computationally cheap but they are not always accurate, and in many cases (e.g., antennas) they are not available. Coarsely-discretized EM models are available for all structures, they are...
Space mapping (SM) is a popular technique that allows creating computationally cheap and reasonably accurate surrogates of EM-simulated microwave structures (so-called fine models) using underlying coarse models, typically equivalent circuits. Here, we consider various ways of enhancing SM surrrogates by exploiting additional training data as well as two function approximation methodologies, kriging...
Space mapping (SM) has been used in microwave engineering for over a decade and demonstrated as one of the most efficient simulation-driven design techniques available to date. By exploiting a fast and physically-based surrogate model, SM allows rapid optimization of an EM-simulated structure of interest (fine model). Several variations of SM algorithms have been proposed including recently introduced...
A computationally efficient algorithm for simulation-driven design optimization of microwave structures is proposed. Our approach exploits variable-fidelity electromagnetic models of the structure under consideration. The low-fidelity model is optimized using a response surface approximation technique. The high-fidelity model is refined by space mapping with polynomial interpolation of the low-fidelity...
Computationally efficient design optimization methodology for ultra-wideband (UWB) antennas is proposed. Our technique exploits space mapping with the underlying surrogate model built using kriging interpolation of the coarse-discretization EM simulation data. Robustness of the proposed approach is demonstrated through the design of two UWB planar antennas. In both cases, an optimized design is obtained...
We introduce a tuning space mapping (TSM) technology for microwave design optimization. For the first time, we formulate the novel TSM concept and show how it relates to the standard space mapping methodology. The new method is based on a so-called tuning model that is created using engineering expertise and knowledge of the design problem, but also utilizes the efficiency of space mapping for translating...
An enhancement of the space mapping (SM) surrogate model through support vector regression is presented. This technique uses a standard SM model (trend function) and support vector regression to model the residuals between the fine model and the standard model. The latter is implemented as a additive output SM term. The proposed methodology offers efficient utilization of the available fine model...
A new space mapping optimization algorithm for microwave design is presented. We implement a distributed fine model evaluation through independent processing of the fine model responses corresponding to consecutive frequency samples using a number of processors. This allows us to obtain a substantial reduction of the overall optimization time for the space mapping algorithm. When our technique is...
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