Estimation of distributed parameters in permittivity models of composite dielectric materials using reflectance

Abstract

We investigate the feasibility of quantifying properties of a composite dielectric material through the reflectance, where the permittivity is described by the Lorentz model in which an unknown probability measure is placed on the model parameters. We summarize the computational and theoretical framework (the Prohorov metric framework) developed by our group in the past two decades for nonparametric estimation of probability measures using a least-squares method, and point out the limitation of the existing computational algorithms for this particular application. We then improve the algorithms, and demonstrate the feasibility of our proposed methods by numerical results obtained for both simulated data and experimental data for inorganic glass when considering the resonance wavenumber as a distributed parameter. Finally, in the case where the distributed parameter is taken as the relaxation time, we show using simulated data how the addition of derivative measurements improves the accuracy of the method.

Document Details

Document Type
Pub Defense Publication
Publication Date
May 23, 2015
Source ID
10.1515/jiip-2014-0061

Entities

People

  • H. Thomas Banks
  • Jared Catenacci
  • Shuhua Hu

Organizations

  • Air Force Office of Scientific Research
  • Army Research Office
  • National Institute of Allergy and Infectious Diseases
  • National Science Foundation
  • North Carolina State University
  • United States Department of Education

Tags

Readers

  • Computational Modeling and Simulation
  • Materials Science and Engineering.
  • Statistical inference.