On Tertiary X-Radiation, Etc by Clark G. L.

By Clark G. L.

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2c and d where we see no essential differences of the gain patterns of the two models. 7 c d 30 60 60 90 10 0 47 −10 −20 [dB] −20 −10 0 90 10 30 0 30 60 90 10 60 0 −10 −20 [dB] −20 −10 0 90 10 Fig. , HFSS (2010), CST Microwave Studio (2013), and FEKO (2011), are extensively used in the modern antenna design in both industry and academia (Kempel 2007). Not long time ago, discrete EM simulators were used mostly for design verification purposes. Nowadays, due to the progress in computing hardware as well as development of computational electromagnetic methods, the discrete EM simulators turn to be indispensable for the entire design process starting from a concept estimation step.

An example of a substrate integrated half-mode 5 GHz antenna shown in Fig. 1 illustrates differences in its responses evaluated with models of different fidelity as well as sensitivity of the antenna responses on the model fidelity. Both of the models are defined, discretized, and simulated using CST MWS (CST Microwave Studio 2013). 33 GHz 8 core CPU with 8 GB RAM computer. A quite dense discretization of the model, which turns in a substantial simulation time, is a result of ensuring no feasible changes of the response versus discretization density.

The last two exploit radial basis function surrogates rather than kriging. Chapter 4 Methodologies for Variable-Fidelity Optimization of Antenna Structures In this chapter, we formulate and discuss several surrogate-based optimization techniques and algorithms that may be useful for computationally efficient antenna optimization. All methods presented here exploit variable-fidelity EM simulations. In particular, in order to optimize the high-fidelity EM model Rf of the antenna structure under consideration, an auxiliary low-fidelity model Rc is utilized that is normally based on coarse-discretization EM evaluation of the same structure.

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