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.
- Heat Transfer Division and Electronic and Photonic Packaging Division
Inverse Estimation of Surface Temperature in Nanoscale Using the Artificial Neural Network
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Jung, BS, Kim, SK, & Lee, WI. "Inverse Estimation of Surface Temperature in Nanoscale Using the Artificial Neural Network." Proceedings of the 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. pp. 403-410. ASME. https://doi.org/10.1115/HT2005-72384
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