Prediction of weld-induced distortion of large structure using equivalent load technique
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
Published online on June 01, 2016
Abstract
Angular distortion in fusion welded joints is an alarming issue which affects the stability and life of the welded structures, occurs due to the changes in the temperature gradient during the welding process. This degrades the dimensional quality of a large structure during assembly which leads to rework the products and hence decreases the productivity. Predicting the weld-induced residual deformation before the production saves the valuable time and resources for rework. The conventional coupled transient, nonlinear, elasto-plastic thermo-mechanical analysis involves huge computational time. Computing a weld sample of small size with single pass itself takes several hours, which will be a huge amount of time in case of large structures consisting of several welding passes; thus, there is a real need of an efficient alternative technique to predict the post-weld distortions. In this work, an attempt has been made to determine the deformation in a submerged arc welded structure using equivalent load technique which reduces the total analysis time by one-third of the conventional techniques in case of a small weld structure. In this proposed method, the transient nonlinear elasto-plastic structural analysis part which is the major time-consuming part of analysis has been almost eliminated. So, this method can effectively use to predict the weld-induced distortion of very large structure with a computation time almost equal to the time required for transient thermal analysis of a small weld structure only. It is not feasible to analyze such a large welded structure with conventional coupled transient, elasto-plastic, nonlinear thermo-mechanical analysis. The predicted results of distortions have been validated with the experimental as well as published results and good agreements have been found.