Adjust the Thermo-Mechanical Properties of Finite Element Models Welded Joints Based on Soft Computing Techniques

• Published in: Hybrid Artificial Intelligent Systems Vol. 10334; pp. 699 - 709
• Main Authors: Fernández Martinez, Roberto, Lostado Lorza, Rubén, Corral Bobadilla, Marina, Escribano Garcia, Rubén, Somovilla Gomez, Fátima, Vergara González, Eliseo P.
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Angular distortion; Finite element method; Genetic algorithms; Multi-objective optimization; Support vector machines; Welding temperature distribution
• ISBN: 3319596497; 9783319596495
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-59650-1_59

An appropriate characterization of the thermo-mechanical behavior of elastic-plastic Finite Element (FE) models is essential to ensure realistic results when welded joints are studied. The welded joints are subject to severe angular distortion produced by an intense heat concentration on a very small area when they are manufactured. For this reason, the angular distortion and the temperature field, which the joints are subjected, is very difficult to model with the Finite Element Method (FEM) when nonlinear effects such as plasticity of the material, radiation and thermal contacts are considered. This paper sets out a methodology to determine the most appropriate parameters needed for modelling the thermo-mechanical behavior in welded joints FE models. The work is based on experimental data (temperature field and angular distortion) and the combined use of Support Vector Machines (SVM) and Genetic Algorithms (GA) with multi-objective functions. The proposed methodology is applied for modelling Butt joint with single V-groove weld manufactured by Gas Metal Arc Welding (GMAW) process when the parameters of speed, current and voltage are, respectively, 6 mm/sec 140 amps and 26 V.