Stochastic-Galerkin Finite-Difference Time-Domain for Waves in Random Layered Media

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The authors introduce a Stochastic Finite-Difference Time Domain solver formulation based on Stochastic Galerkin Method. The solver can calculate the statistics of the wave in time domain, including mean, standard deviation at each time step. The method uses a single simulation of an expanded system, without the need for repeated simulations like Monte Carlo analysis. We demonstrate the method is accurate for computing random total waves in layered media with Gaussian random permittivity and conductivity. We also demonstrate the method for simulating materials with Bernoulli distributed random profiles, which is used to model material that may or may not exist. Results accuracy and computation time compare favorably to Monte Carlo simulations.

Original languageEnglish (US)
Title of host publication2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728169668
DOIs
StatePublished - Dec 7 2020
Event2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020 - Hangzhou, China
Duration: Dec 7 2020Dec 9 2020

Publication series

Name2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020

Conference

Conference2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2020
Country/TerritoryChina
CityHangzhou
Period12/7/2012/9/20

Keywords

  • Computational electromagnetic
  • finite-difference time-domain (FDTD)
  • polynomial chaos
  • random media
  • uncertainty analysis
  • uncertainty quantification

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Electronic, Optical and Magnetic Materials
  • Control and Optimization
  • Modeling and Simulation
  • Instrumentation

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