Abstract
The prediction of welding distortion requires expertise in computer simulation programs, a clear definition of the nonlinear material properties, and mesh settings together with the nonlinear solution settings of a coupled thermal–structural analysis. The purpose of this paper is to present the validation of an automatic simulation tool implemented in Ansys using Python scripting. This tool allows users to automate the preparation of the simulation model with a reduced number of inputs. The goal was, based on some assumptions, to provide an automated simulation setup that enables users to predict accurate distortion during the welding manufacturing process. Any geometry prepared in a CAD software can be used as the input, which gave us much geometrical flexibility in the shapes and sizes to be modeled. A thermomechanical loosely coupled analysis approach together with element birth and death technology was used to predict the distortions. The automation of the setup enables both simulation and manufacturing engineers to perform welding-induced distortion prediction. The results showed that the method proposed predicts distortion with 80–98% accuracy.
Highlights
The purpose of this paper is to present the validation of an automatic simulation tool implemented in Ansys using Python scripting
Welding distortion is defined as the distortion caused by the nonuniform expansion and contraction of the weld and base metal during the heating and cooling cycle produced by a welding process
This input needs to be modeled as a moving load over time through the geometry; Element deactivation and activation logic during the welding process
Summary
Welding distortion is defined as the distortion caused by the nonuniform expansion and contraction of the weld and base metal during the heating and cooling cycle produced by a welding process. This is an undesirable and mostly inevitable permanent change in shape, which can usually be managed by constraining the parts or changing the welding process. Trial and error tests were used to solve these problems. Digital tools involving finite element simulations and databases can greatly reduce the calculation time and increase the number of possible numerical tests, as well as the accuracy of the results [1]
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