Machine Learning Control Design for Elastic Composite Materials

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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A novel numerical method, based on a machine learning approach, is used to solve an inverse problem involving the Dirichlet eigenfrequencies for the elasticity operator in a bounded domain filled with a composite material. The inhomogeneity of the material under study is characterized by a vector which is designed to control the constituent mixture of homogeneous elastic materials that compose it. Using the finite element method, we create a training set for a forward artificial neural network, solving the forward problem. A forward nonlinear map of the Dirichlet eigenfrequencies as a function of the vector design parameter is then obtained. This forward relationship is inverted and used to obtain a training set for an inverse radial basis neural network, solving the aforementioned inverse problem. A numerical example showing the applicability of this methodology is presented.

Original languageEnglish
Title of host publicationComputational Science – ICCS 2021 - 21st International Conference, Proceedings
EditorsMaciej Paszynski, Dieter Kranzlmüller, Dieter Kranzlmüller, Valeria V. Krzhizhanovskaya, Jack J. Dongarra, Peter M.A. Sloot, Peter M.A. Sloot, Peter M.A. Sloot
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages15
ISBN (Print)9783030779634
StatePublished - 2021
Event21st International Conference on Computational Science, ICCS 2021 - Virtual, Online
Duration: 16 Jun 202118 Jun 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12743 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference21st International Conference on Computational Science, ICCS 2021
CityVirtual, Online


  • Composite materials
  • Eigenfrequencies of the elasticity operator
  • Finite element method
  • Inverse problems
  • Machine learning


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