Abstract
Laser welding (LW) becomes one of the most economical high quality joining processes. LW offers the advantage of very controlled heat input resulting in low distortion and the ability to weld heat sensitive components. To exploit efficiently the benefits presented by LW, it is necessary to develop an integrated approach to identify and control the welding process variables in order to produce the desired weld characteristics without being forced to use the traditional and fastidious trial and error procedures. The paper presents a study of weld bead geometry characteristics prediction for laser overlap welding of low carbon galvanized steel using 3D numerical modelling and experimental validation. The temperature dependent material properties, metallurgical transformations and enthalpy method constitute the foundation of the proposed modelling approach. An adaptive 3D heat source is adopted to simulate both keyhole and conduction mode of the LW process. The simulations are performed using 3D finite element model on commercial software. The model is used to estimate the weld bead geometry characteristics for various LW parameters, such as laser power, welding speed and laser beam diameter. The calibration and validation of the 3D numerical model are based on experimental data achieved using a 3 kW Nd:Yag laser system, a structured experimental design and confirmed statistical analysis tools. The results reveal that the modelling approach can provide not only a consistent and accurate prediction of the weld characteristics under variable welding parameters and conditions but also a comprehensive and quantitative analysis of process parameters effects on the weld quality. The results show great concordance between predicted and measured values for weld bead geometry characteristics, such as depth of penetration, bead width at the top surface and bead width at the interface between sheets, with an average accuracy greater than 95%.
Highlights
The reduction of energy consumption and atmospheric pollution as well as the improvement of safety have led the automotive industry reconsider their design methods in order to decrease the weight of vehicles by using high performance materials
The paper presents a study of weld bead geometry characteristics prediction for laser overlap welding of low carbon galvanized steel using 3D numerical modelling and experimental validation
The present paper describes the development of a 3D numerical model to be used for generating the additional data needed to build the most accurate, flexible and efficient artificial neural network (ANN) based model for predicting the weld bead geometry characteristics in laser overlap welding of low carbon galvanized steel
Summary
The reduction of energy consumption and atmospheric pollution as well as the improvement of safety have led the automotive industry reconsider their design methods in order to decrease the weight of vehicles by using high performance materials. The tailored welded banks are the major components constituting the new vehicle body. This design approach aims to optimize the weight of the vehicle structure by joining sheets from various nuances of high resistance material and different thicknesses. The quantity of welds in the car body was more than doubled in the last years In these conditions, the aptitude of the welds to resist to diverse solicitations remains the main concern of engineers. The aptitude of the welds to resist to diverse solicitations remains the main concern of engineers This aptitude is conditioned largely by the weld cross section geometry characteristics [1]. The identification of the laser parameter adjustments that lead to desired welds characteristics, without being forced to use the traditional and fastidious trial and error procedures, requires accurate and robustly predictive modelling approaches
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