Paper Title:
An Artificial Neural Network Approach to Plastic Collapse of Oval Boiler Tubes
  Abstract

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, 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
Authors
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Price
$32.00
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