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

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Abstract
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 cross-section 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.
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Zarrabi, Khosrow
Basu, Abheek
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Publication Year
2008
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Journal Article
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UNSW Faculty
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download Zarrabi-Basu-AdvancedMaterialsResearch-May2008.pdf 53.75 KB Adobe Portable Document Format
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