An Artificial Neural Network Approach to Plastic Collapse of Oval Boiler Tubes

Abstract:

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Boilers in power, refinery and chemical processing plants contain extensive range of tube bends. Tube bends are manufactured by bending a straight-section tube. As a result, the crosssection of a tube bend becomes oval. Using the finite element analysis (FEA) and artificial neural network (ANN), the paper presents the relationships between the plastic collapse pressures and tube bend dimensions with various degrees of ovality. It is found that as ovality increases the plastic collapse pressure decreases. Also, the reduction of plastic collapse pressure with ovality is small for a thick tube bend when compared with that for a thin tube bend.

Info:

Periodical:

Advanced Materials Research (Volumes 41-42)

Edited by:

Xiaozhi Hu, Brent Fillery, Tarek Qasim and Kai Duan

Pages:

421-426

DOI:

10.4028/www.scientific.net/AMR.41-42.421

Citation:

K. Zarrabi and A. Basu, "An Artificial Neural Network Approach to Plastic Collapse of Oval Boiler Tubes", Advanced Materials Research, Vols. 41-42, pp. 421-426, 2008

Online since:

April 2008

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Price:

$35.00

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