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Inverse Estimation of Surface Temperature in Nanoscale Using the Artificial Neural Network

[+] Author Affiliations
Bup Sung Jung, Woo Il Lee

Seoul National University, Seoul, Korea

Sun K. Kim

Seoul National University of Technology, Seoul, Korea

Paper No. HT2005-72384, pp. 403-410; 8 pages
doi:10.1115/HT2005-72384
From:
  • ASME 2005 Summer Heat Transfer Conference collocated with the ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems
  • Heat Transfer: Volume 1
  • San Francisco, California, USA, July 17–22, 2005
  • Conference Sponsors: Heat Transfer Division and Electronic and Photonic Packaging Division
  • ISBN: 0-7918-4731-4 | eISBN: 0-7918-3762-9
  • Copyright © 2005 by ASME

abstract

An inverse heat conduction problem (IHCP) for nanoscale structures was studied. The conduction phenomenon is modeled using the Boltzmann transfer equation. Phonon-mediated heat conduction in one dimension is considered. One boundary, where temperature observation takes place, is subjected to a known boundary condition and the other boundary is exposed to an unknown temperature. The artificial neural network (ANN) is employed to solve the described inverse problem. Sample results are presented and discussed.

Copyright © 2005 by ASME

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