A 3-D Stochastic FVTD Method Based on Reduced-Order Modeling for Statistically Random Media in Nano-Electromagnetic Applications

Author

Kantartzis, Nikolaos V. ; Zygiridis, Theodoros T. ; Tsiboukis, Theodoros D.

Author_Institution

Dept. of Electr. & Comput. Eng., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece

Volume

51

Issue

3

fYear

2015

fDate

Mar-15

Firstpage

1

Lastpage

5

Abstract

A spectrally optimized stochastic finite-volume time-domain technique is developed in this paper for the consistent analysis of 3-D nanoscale devices with statistically varying media heterogeneities. The novel algorithm is found on a compact block state-space framework and offers single-run evaluations of the mean value and standard deviation, thus evading the excessive system requirements of typical multiple-realization Monte Carlo FDTD approaches. Moreover, an energy-conserving flux concept guarantees the precise discretization of electromagnetic fields in regions of abrupt geometric details. In this manner, the complicated structure of nanocomposite applications is very reliably modeled, even for sub-wavelength field uncertainties, as deduced by several numerical configurations.

Keywords

electromagnetic fields; finite volume methods; nanocomposites; random processes; statistical analysis; stochastic processes; time-domain analysis; 3D nanoscale devices; 3D stochastic FVTD method; compact block state-space framework; electromagnetic field discretization; energy-conserving flux; mean value; multiple-realization Monte Carlo FDTD approaches; nanocomposite; nanoelectromagnetic applications; reduced-order modeling; single-run evaluations; spectrally optimized stochastic finite-volume time-domain technique; standard deviation; statistically random media; statistically varying media heterogeneities; subwavelength field uncertainties; Magnetic materials; Media; Metamaterials; Nanoscale devices; Stochastic processes; Time-domain analysis; Uncertainty; Finite-volume time-domain (FVTD) methods; model-order reduction schemes; nano-electromagnetics; stochastic/statistically varying techniques;

fLanguage

English

Journal_Title

Magnetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9464

Type

jour

DOI

10.1109/TMAG.2014.2356411

Filename

7093502