Abstract
Simulated-driven optimization plays a vital role in the optimal design of engineering systems. The presented work in this chapter considers approaches for obtaining the optimal design of some photonic crystal (PC) nanostructures. PCs are periodic dielectric/dielectric or dielectric/metallic nanostructures manipulating the flow of light. They are one of the most emerging physical systems that have attracted the attention of engineers and scientists, in the last few decades, for their promising applications in many areas. Two optimization approaches are used for achieving the optimal design of one-dimensional (1D) PC nanostructures. The first approach is based on minimax optimization criterion that best fits the design specifications, while the second one is based on design centering criterion, to maximize the probability of satisfying design specifications. The proposed approaches allow considering problems of higher dimensions, in addition, optimizing over the PC layers’ thickness and/or its material type. Two practical examples are given to demonstrate the flexibility and efficiency of these approaches. The first is a 1D PC-based optical filter operating in the visible range. The second example is a 1D PC-based spectral control filter, working in the infrared range, and enhances the efficiency of thermophotovoltaic systems.
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Acknowledgments
Authors would like to thank Prof. Slawomir Koziel, School of Science and Engineering, Reykjavik University, for his invitation to contribute to this book. Authors also would like to acknowledge the contributions to the original work by, Eng. Mahmoud Taha Maghrabi, Faculty of Engineering, Cairo University, now with Electrical and Computer Engineering Department, McMaster University, which has been reviewed in this chapter.
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Hassan, AK.S.O., Rafat, N.H., Mohamed, A.S.A. (2016). Optimal Design of Photonic Crystal Nanostructures. In: Koziel, S., Leifsson, L., Yang, XS. (eds) Simulation-Driven Modeling and Optimization. Springer Proceedings in Mathematics & Statistics, vol 153. Springer, Cham. https://doi.org/10.1007/978-3-319-27517-8_10
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