
A semi-analytical method for the calculation of double-ellipsoidal heat source parameters in welding simulation
Author(s) -
S. Trupiano,
Valerio G. Belardi,
Pierluigi Fanelli,
Luca De Gaetani,
Francesco Vivio
Publication year - 2022
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1214/1/012023
Subject(s) - welding , ellipsoid , residual stress , finite element method , process (computing) , computer simulation , gas tungsten arc welding , thermal , work (physics) , computer science , mechanical engineering , mechanics , structural engineering , materials science , simulation , engineering , arc welding , thermodynamics , physics , metallurgy , astronomy , operating system
Structural integrity assessment of welded components requires the determination of residual stress and deformations induced by the welding process. The implementation of both a numerical static mechanical analysis and a thermal transient analysis is needed in order to accurately determine stress and strain fields. The most faithful representation of the heat flow provided by the welding torch in thermal simulations is realized with Goldak’s double ellipsoid, especially in case of MIG/MAG and combined TIG-MIG/MAG welding. The correct determination of the temperature trends during the welding process simulation is essential for the subsequent mechanical FEA. In order to obtain the above-mentioned temperature trends, some parameters must be determined ex ante, e.g., the geometrical characteristics of Goldak’s double ellipsoid. Generally, a large number of trial simulations must be performed in order to define these parameters. However, manual fitting is often complicated. To overcome such difficulties, in this work, it is reported a combined analytical and numerical method to determine the parameters using the genetic algorithm NSGA-II. First-attempt parameters are obtained through the solution of the Fachinotti’s analytical formulation. This first stage requires a restricted set of experimental data, such as weld pool extension and one temperature trend in the proximity of the seam. Afterwards, first-attempt parameters and experimental data are used to determine the final parameters by means of a set of numerical thermal simulations guided through the genetic algorithm optimization. To confirm the good-functioning of the method, a numerical analysis for the simulation of the experimental data and another FE simulation performed with the final results of the method are presented.