Draft: Computational Optimization of Arc Welding Parameters Using Coupled Genetic Algorithms and Finite Element Method
نویسندگان
چکیده
An effective and rigorous approach to determine optimum welding process parameters is implementation of advanced computer aided engineering (CAE) tool that integrates efficient optimization techniques and numerical welding simulation. In this paper, an automated computational methodology to determine optimum arc welding process control parameters is proposed. It is a coupled Genetic Algorithms (GA) and Finite Element (FE) based optimization method where GA directly utilizes output responses of FE based welding simulations for iterative optimization. Effectiveness of the method has been demonstrated by predicting optimum parameters of a lap joint specimen of two thin steel plates for minimum distortion. Three dimensional FE model has been developed to simulate the arc welding process and validated by experimental results. Subsequently, it is used by GA as the evaluation model for optimization. The optimization results show that such a CAE based method can predict optimum parameters successfully with limited effort and cost.
منابع مشابه
Investigating the Effect of Joint Geometry of the Gas Tungsten Arc Welding Process on the Residual Stress and Distortion using the Finite Element Method
Although a few models have been proposed for 3D simulation of different welding processes, 2D models are still more effective in design goals, thus more popular due to the short-time analysis. In this research, replacing "time" by the "third dimension of place", the gas tungsten arc welding process was simulated by the finite element method in two dimensions and in a short time with acceptable ...
متن کاملSimulation-based numerical optimization of arc welding process for reduced distortion in welded structures
This paper presents an effective numerical approach for welding process parameter optimization to minimize weld-induced distortion in structures. A numerical optimization framework based on coupled Genetic Algorithm (GA) and Finite Element Analysis (FEA) is developed and implemented for a low and a high fidelity model. Classical weakly coupled thermo-mechanical analysis with thermo-elasto-plast...
متن کاملPareto Optimization of Two-element Wing Models with Morphing Flap Using Computational Fluid Dynamics, Grouped Method of Data handling Artificial Neural Networks and Genetic Algorithms
A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...
متن کاملThe evolutionary optimization of selected welded structures
Purpose: of this paper is to present the recent possibility of evolutionary optimization method application to predicting the proper welding parameters in the weld process. The objective of the welding simulation is to study the temperature generated during the welding process and to investigate residual stresses in the component after the welding. Such results give the possibility to determine...
متن کاملThe Optimization of the Effective Parameters of the Die in Parallel Tubular Channel Angular Pressing Process by Using Neural Network and Genetic Algorithm Methods
One of reasons that researchers in recent years have tried to produce ultrafine grained materials is producing lightweight components with high strength and reliability. There are disparate methods for production of ultra-fine grain materials,one of which is severe plastic deformation method. Severe plastic deformation method comprises different processes, one of which is Parallel tubular chann...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013