A Study on the Prediction of Ship Plate Distortion Topology by Neural Networks

Abstract

Ship plate distortion results in a decrease in strength and aesthetics, has a detrimental effect on the fabrication process, as well as an increase in production cost due to the need for correction. Welding heat has been regarded as a major contributor to distortion. Assessing the distortion problem, without making assumptions, is extremely difficult due to the complexity of the variables involved, e.g., welding procedures, materials, design, and geometry. This paper develops a neural network model to predict the topology of ship plate distortion. The developed model presents good agreement with actual distortion data that have been obtained. In terms of variable sensitivity, chemical composition should be taken into account.