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Eingeladener Vortrag
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Simultaneous measurement of tool torque, traverse force and axial force in friction stir welding
(2013)
Simultaneous measurement of the tool torque, traverse force and axial force during friction stir welding process is of great significance to the understanding of the underlying process mechanism and the optimizing of the process parameters. Different from the traditional measurement methods using load cell or rotating component dynamometer, an indirect but economical methodology is used in this study for the simultaneous measurement of the traverse force, axial force and tool torque by monitoring the output torques of the servo motors and main spindle three-phase AC induction motor inside the FSW machine. The values of the traverse force, axial force and tool torque are determined under different welding conditions, and the influencing factors are examined. The measured results in friction stir welding of AA2024-T4 aluminum alloys at different combinations of tool rotation speed and welding speed lay foundation for process optimization.
Microcrack formation during gas metal arc welding of high-strength fine-grained structural steel
(2014)
The recent development of high-performance-modified spray arc processes in gas metal arc welding due to modern digital control technology and inverter power sources enables a focused spray arc, which results in higher penetration depths and welding speed. However, microcracks occurred in the weld metal while approaching the process limits of the modified spray arc, represented by a 20-mm double layer DV-groove butt-weld. These cracks were detected in structural steel exhibiting a yield strength level of up to 960 MPa and are neither dependent on the used weld power source nor a consequence of the modified spray arc process itself. The metallographic and fractographic investigations of the rather exceptional fracture surface lead to the classification of the microcracks as hot cracks. The effects of certain welding parameters on the crack probability are clarified using a statistical design of experiment. However, these microcracks do not impact the design specification for toughness in the Charpy V-notch test (absorbed energy at -40 °C for the present material is 30 J).
Despite the advances in hardware and software techniques, standard numerical methods fail in providing real-time simulations, especially for complex processes such as additive manufacturing applications. A real-time simulation enables process control through the combination of process monitoring and automated feedback, which increases the flexibility and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in the form of a beadon-plate experiment is performed to get a first insight into the process and to set parameters suitably. In this work, a reduced order model for the transient thermal problem of the bead-on-plate weld simulation is developed, allowing an efficient model calibration and control of the process. The proposed approach applies the proper generalized decomposition (PGD) method, a popular model order reduction technique, to decrease the computational effort of each model evaluation required multiple times in parameter estimation, control, and optimization. The welding torch is modeled by a moving heat source, which leads to difficulties separating space and time, a key ingredient in PGD simulations. A novel approach for separating space and time is applied and extended to 3D problems allowing the derivation of an efficient separated representation of the temperature.
The results are verified against a standard finite element model showing excellent agreement. The reduced order model is also leveraged in a Bayesian model parameter estimation setup, speeding up calibrations and ultimately leading to an optimized real-time simulation approach for welding experiment using synthetic as well as real measurement data.
Despite the advances in hardware and software techniques, standard numerical methods fail in providing real-time simulations, especially for complex processes such as additive manufacturing applications. A real-time simulation enables process control through the combination of process monitoring and automated feedback, which increases the flexibil- ity and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in form of a bead-on- plate experiment is performed to get a first insight into the process and to set parameters suitably. In this work, a reduced order model for the transient thermal problem of the bead-on-plate weld simulation is devel- oped, allowing an efficient model calibration and control of the process. The proposed approach applies the proper generalized decomposition (PGD) method, a popular model order reduction technique, to decrease the computational effort of each model evaluation required multiple times in parameter estimation, control and optimization. The welding torch is modeled by a moving heat source, which leads to difficulties separating space and time, a key ingredient in PGD simulations. A novel approach for separating space and time is applied and extended to 3D problems allowing the derivation of an efficient separated representation of the tem- perature. The results are verified against a standard finite element model showing excellent agreement. The reduced order model is also leveraged in a Bayesian model parameter estimation setup, speeding up calibrations and ultimately leading to an optimized real-time simulation approach for welding experiment using synthetic as well as real measurement data.