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A Novel Methodology for Combined Parameter and Function Estimation Problems

[+] Author Affiliations
Ali Hakkaki-Fard

McGill University, Montreal, QC, Canada

Hosein Molavi

Tarbiat Modares University, Tehran, Tehran, Iran

Ramin K. Rahmani

The University of Toledo, Toledo, OH

Paper No. HT2009-88400, pp. 507-519; 13 pages
doi:10.1115/HT2009-88400
From:
  • ASME 2009 Heat Transfer Summer Conference collocated with the InterPACK09 and 3rd Energy Sustainability Conferences
  • Volume 1: Heat Transfer in Energy Systems; Thermophysical Properties; Heat Transfer Equipment; Heat Transfer in Electronic Equipment
  • San Francisco, California, USA, July 19–23, 2009
  • Conference Sponsors: Heat Transfer Division
  • ISBN: 978-0-7918-4356-7 | eISBN: 978-0-7918-3851-8
  • Copyright © 2009 by ASME

abstract

This article presents a novel methodology, which is highly efficient and simple to implement, for simultaneous retrieval of a complete set of thermal coefficients in combined parameter and function estimation problems. Moreover, the effect of correlated parameters on convergence performance is examined. The present methodology is a combination of two different methods: The Conjugate Gradient Method with Adjoint Problem (CGMAP) and Box-Kanemasu method (BKM). The methodology uses the benefit of CGMAP in handling function estimation problems and BKM for parameter estimation problems. One of the unique features about the present method is that the correlation among the separate unknowns does not behave as a limiting factor to the convergence of the problem. Numerical experiments using measurement errors are performed to verify the proposed method in solving the combined parameter and function estimation problems. The obtained results show that the combined procedure can efficiently and reliably estimate the values of the thermal coefficients.

Copyright © 2009 by ASME

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