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Application of Neural Network to the Estimation of Curvature Deformation of Steel Plates in Line Heating  

Jeon, Byung-Jae (Mastek Heavy Industry Co. Ltd.)
Kim, Hyun-Jun (Far East Ship Design & Engineering Co. Ltd)
Yang, Park-Dal-Chi (School of Naval Architecture and Ocean Engineering, Univ. of Ulsan)
Publication Information
Journal of Ocean Engineering and Technology / v.20, no.4, 2006 , pp. 24-30 More about this Journal
Abstract
Different methods exist for the estimation of thermaldeformation of plates in the line heating process. These are based on the assumption of residual strains in the heat-affected zone, known as the method of inherent strains, or simulated relations between heating conditions and residual deformations. The purpose of this paper is to develop a simulator of thermal deformation in the line heating, using the artificial neural network. Curvature deformations for the plate-forming are investigated, which can be used as a prime deformation parameter in the process. The curvature of plates are calculated using the approximation of plate surface by NURBS. Line heating experiments for 11 specimens of different thickness and heating conditions were performed. Two neural networks predicting the maximum temperature and curvature deformations at the heating line are studied. It was concluded that the thermal deformations predicted by the neural network can be used in a line heating simulator, which is considered an attractive and practical alternative to the existing methods.
Keywords
Line heating; Curvature deformation; Gaussian curvature; Neural network;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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