Encyclopedie de la recherche sur l'aluminium au Quebec - Edition 2014 | Page 64

62 TRANSFORMATION ET APPLICATIONS // TRANSFORMATION AND APPLICATIONS Numerical Simulation of Friction Stir Welding with Smoothed Particle Hydrodyamics SIMULATION NUMÉRIQUE DU SOUDAGE PAR FRICTION MALAXAGE AVEC LA MÉTHODE « SMOOTHED PARTICLE HYDRODYNAMICS » Simulation numérique du soudage par friction malaxage avec la méthode ‘smoothed particle NUMERICAL SIMULATION OF FRICTION STIR WELDING WITH hydrodynamics’ SMOOTHED PARTICLE HYDRODYNAMICS Kirk Fraser, Lyne St-Georges and László I. Kiss Université de Québec à Chicoutimi (UQAC) Joining of aluminum alloys via friction stir welding (FSW) is gaining widespread acceptance. The process’s ability to create high strength welds in a solid state with few imperfections makes the method very appealing for industrial and commercial applications. More recently, a double sided FSW process was developed using a bobbin tool. One of the main advantages of this approach is that hollow core sections can be welded. Also, the vertical force on the machine is zero. The results from the simulation are shown below. A comparison of the shape of the finished weld for the simulation and from experiment is provided. We can see a close agreement between the real and simulated welds. Fraser et al. [6,7] showed that the welding defects can be simulated for different process parameters. The required torque to sustain 800rpm was measured and compared for the simulation and experiment, we show that an excellent correlation is obtained between the two. A coupled thermo-mechanical model has been created using the smoothed particle hydrodynamics approach in LS-DYNA. The model simulates advancing phase of the double sided process. Once fully validated, the model will be used to perform parametric studies to determine the optimum welding parameters. Tail Length (mm) Simulation 1 - 600 RPM 800 mm/min 50.0 Experiment 3 - 600 RPM 800 mm/min 45.0 Blowout Hole (mm) 20.0 18.0 25.0 15.0 Blowout Protrusion (Advancing side, mm) Blowout Protrusion (Retreating side, mm) Rate of rotation, forward advancement speed as well as design of the shape of the FSW tool can be optimized. The model can qualitatively and quantitatively determine the quality and strength of the weld. Max Torque (N m) Distance to Form Weld (mm) -8.0 6.0 20.0 18.9 35.0 20.0 Image from [5] Numerical simulation of the FSW process is complicated by the large plastic deformation that the aluminum work pieces undergo. Typical finite element methods (mesh based) are not able to accurately capture this behavior due to the excessive distortion of elements in the large deformation zone. The SPH method is a mesh-free method, the elements are not confined to a fixed grid, this allows for accurate simulation of the large deformation process. One of the major attractions to the SPH method is that the formulation is Lagrangian, thus tracking of the time history of all the field variables is easily accomplished. The rate of change of the field variables for a given particle “i”, with N “j” neighbors in the support domain is given by Lui and Lui [4]; There are three major flaws that are visible in the bobbin tool weld track: 1) start of weld tail, 2) lead in distance to form the weld and 3) blowout region at tool exit. These defects are nicely captured by the SPH simulation The temperature results are shown in the adjacent image. The hottest region is found directly under the tool, the shape of the temperature profile is strongly influenced by the flow of the aluminum material and vice-versa. Wi,j = Smoothing Function πi,j = Artificial Viscosity Hi = Artificial Heat The aluminum work pieces are modeled using SPH elements. The supporting apparatus and the FSW tool are modeled using rigid bodies meshed with hexahedral finite elements. Here we consider a short section of a hollow core HSS tube. The aluminum material is modeled using the Johnson-Cook constitutive material law. The flow stress is given by [3]; Kirk Fraser Lyne St-Georges László I. Kiss Université du Québec à Chicoutimi • The developed numerical model can be used as a powerful process diagnostic tool for friction stir welding. The model • Welding defects such cavities, lack of penetration, and incomplete welding can be predicted. An iterative viscoplastic formulation is used such that; financial support and GRIPS for their technical support. will help to determine the optimal process parameters to create high quality welds for the double sided FSW process. • Residual stresses and strains can be determined. • The ultimate strength, hardness and resistance of the weld can be evaluated. • The author would like to acknowledge l’Université de Québec à Chicoutimi (UQAC), NSERC, and CQRDA for their Tool motion The relation between pressure and volume is modeled by the Gruneisen equation of state; • We are currently developing a coupled computational solid mechanics and heat transfer code using the SPH method. The code is written to take advantage of the inherent parallel nature of the graphics processing unit (GPU). A spall failure model is used to effectively simulate the material after local failure is determined. The spall model sets the deviatoric stresses to zero when the pressure in the element surpasses the pressure cutoff. Subsequently only compressive stresses are allowed. Following failure, the material behaves as rubble. Heat is generated by the friction between the tool and the aluminum as well as the transformation of plastic work to heat. Plate Advance Angular Thickness Rate Velocity 1/2 600 800 in mm/min rpm Value Units Material Constants Johnson-Cook Parameters [1] Thermal Parameters Gruneisen EOS Parameters [2] ρ0 G A B C n m Cv K C0 S1 γ0 a 6061 T6 2700 27.6 324