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    Friction stir welding of spheres, cylinders, and T-joints: design, experiment, modelling, and analysis

    Lammlein, David Hunter
    : https://etd.library.vanderbilt.edu/etd-10222010-154532
    http://hdl.handle.net/1803/14350
    : 2010-11-09

    Abstract

    Friction Stir Welding (FSW) is a high quality joining process which is currently limited by its range of application. Four experiments are presented which demonstrate expanded application of FSW. Included with these studies are computational models which reliably predict temperature gradients, material flow, and process forces. The ability to predict process conditions prior to joining is valuable because obtaining experimental data is resource intensive in FSW. In blind T-joints, the vertical member can be a large plate or sheet which obstructs observation of the horizontal member or rib, which itself can be lengthy or curved. In a manufacturing setting, a method of jointline tracking is necessary to apply FSW to the task. Here a method based on process force feedback control of lateral tool position is used to effectively follow the jointline. Computational models are presented which can be used to evaluate the tractability of a process geometry as well as provide axial force versus lateral position data for tracking. Conical FSW tools present a simple and durable design capable of variable penetration welding and tool extraction without defect. An experiment is presented which achieves good weld appearance and strength using the tool. Spheres are useful primarily as compression vessels. FSW of small radius, butted hemispheres is demonstrated here using a cupped shoulder tool with excellent superficial appearance and high tensile strength. A conical tool is used in partial penetration for applications where internal supports are unacceptable. The FSW of pipes expands use to fossil fuel industries. Successful FSW on small diameter pipe is demonstrated using a scrolled shoulder, threaded probe tool offset in the leading direction with respect to the pipe. Corresponding computational models are presented for these processes which reliably predict process conditions.
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