NDLI: Neural networks for solving the inverse heat transfer problem of continuous casting mould

Content Provider	IEEE Xplore Digital Library
Author	Wang Xudong Yao Man
Copyright Year	2011
Description	Author affiliation: School of Material Science and Engineering, Dalian University of Technology, 116023, China (Wang Xudong; Yao Man)
Abstract	Accurate and real-time detection of mould transient heat transfer is a strong assurance for producing good initial solidification strand and accurately controlling the solidification process in continuous casting. Based on the measured data of mould temperatures during continuous casting of round billet, to decrease the calculation time for meeting the online monitoring and calculation requirement, the feasibility of using neural networks to solve the inverse problem of heat transfer for continuous casting mould was discussed. The results show that the neural network is faster for inverse model, and the calculation results by this method can correctly reflect the characteristics of non-uniform heat transfer, which provides a worthwhile and applicable method for online calculation and visual technology of heat transfer and solidification inside continuous casting mould.
Starting Page	791
Ending Page	794
File Size	316034
Page Count	4
File Format	PDF
ISBN	9781424499502
ISSN	21579563
e-ISBN	9781424499533
DOI	10.1109/ICNC.2011.6022280
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Temperature measurement Resistance Temperature distribution Casting inverse problem continuous casting mould process Electrical resistance measurement neural network heat transfer Heat transfer Resistance heating
Content Type	Text
Resource Type	Article

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