On the Design of Complex EM Devices and Systems Through the System-by-Design Paradigm: A Framework for Dealing With the Computational Complexity

The system-by-design (SbD) is an emerging engineering framework for the optimization-driven design of complex electromagnetic (EM) devices and systems. More specifically, the computational complexity of the design problem at hand is addressed by means of a suitable selection and integration of functional blocks comprising problem-dependent and computationally efficient modeling and analysis tools as well as reliable prediction and optimization strategies. Due to the suitable reformulation of the problem at hand as an optimization one, the profitable minimum-size coding of the degrees of freedom (DoFs), and the smart replacement of expensive full-wave (FW) simulators with proper surrogate models (SMs), which yield fast yet accurate predictions starting from minimum size/reduced CPU-costs training sets, a favorable environment for optimal exploitation of the features of global optimization tools in sampling wide/complex/nonlinear solution spaces is built. This research summary is then aimed at: 1) providing a comprehensive description of the SbD framework and of its pillar concepts and strategies; 2) giving useful guidelines for its successful customization and application to different EM design problems characterized by different levels of computational complexity; and 3) envisaging future trends and advances in this fascinating and high-interest (because of its relevant and topical industrial and commercial implications) topic. Representative benchmarks concerned with the synthesis of complex EM systems are presented to highlight advantages and potentialities as well as current limitations of the SbD paradigm.

Automated summary

The system-by-design (SbD) is an emerging engineering framework that addresses the computational complexity of complex electromagnetic (EM) devices and systems through the integration of functional blocks and optimization strategies. It provides a favorable environment for optimal exploitation of global optimization tools in sampling wide/complex/nonlinear solution spaces. This research summary provides a comprehensive description of the SbD framework, guidelines for customization and application, and future trends in this high-interest topic.