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Identification of a Steady-State Flow in Porous Media Using Artificial Neural Networks

[+] Author Affiliations
Marek J. Lefik

Technical University of Łódz, Łódz, Poland

Daniela P. Boso, Bernhard A. Schrefler

Università di Padova, Padova, Italy

Paper No. ESDA2012-82948, pp. 89-95; 7 pages
doi:10.1115/ESDA2012-82948
From:
  • ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis
  • Volume 1: Advanced Computational Mechanics; Advanced Simulation-Based Engineering Sciences; Virtual and Augmented Reality; Applied Solid Mechanics and Material Processing; Dynamical Systems and Control
  • Nantes, France, July 2–4, 2012
  • Conference Sponsors: International
  • ISBN: 978-0-7918-4484-7
  • Copyright © 2012 by ASME

abstract

For a steady state convection problem, assuming given concentration field values in a few measurement points and hydraulic head values in the same piezometers, the source of the concentration, and its intensity are deduced using Artificial Neural Networks (ANNs). ANNs are trained with data extracted from Finite Difference (FD) solution of a classical convection problem for small Peclet number. The numerical analysis is exemplified for vanishing, homogeneous and non-homogeneous field of velocity. It is shown that the diffusivity vector can also be identified. The complexity of the problem is discussed for each studied case.

Copyright © 2012 by ASME

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