Ingenieurwissenschaften und zugeordnete Tätigkeiten
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Laser metal deposition (LMD) has been applied as a coating technology for many years. Today, the technologies capacity to produce 3D depositions leads to a new field of application as additive manufacturing method. In this paper, 3D laser metal deposition of titanium alloy Ti-6Al-4V is studied with special regard to the demands of additive manufacturing. Therefore, only the coaxial LMD powder nozzle is used to create the shielding gas atmosphere, which ensures high geometric flexibility. Furthermore, specimen with high aspect ratio and hundreds of layers are manufactured, which represent typical features in additive manufacturing. The presented study contains the following steps: First, cylindrical specimens are manufactured with a standard shell-core build-up strategy and mechanical properties as well as fracture mechanisms are determined. Based on the results, experiments are conducted to improve the build-up strategy and new tensile test specimens are built with the improved strategy. The improved strategy incorporates variable track overlap ratios to achieve a constant growth in the shell and core area. As blanks, lean cylinders comprising more than 240 layers and a height of more than 120mm are manufactured. The specimens are analyzed by X-ray inspection for material defects. Fractured surfaces are observed via scanning electron microscopy and the composition of the surfaces is determined using energy dispersive X-ray spectroscopy. The tensile test results prove mechanical properties close to ASTM F1108 specification for wrought material.
New developments in nickel-based superalloys and production methods, such as the use of additive manufacturing (AM), can result in innovative designs for turbines. It is crucial to understand how the material behaves during the AM process to advance industrial use of these techniques. An analytical model based on reaction-diffusion formalism is developed to better explain the solidification behavior of the material during laser metal deposition (LMD). The well-known Scheil-Gulliver theory has some drawbacks, such as the assumption of equilibrium at the solid-liquid interface, which is addressed by this method. The solidified fractions under the Scheil model and the pure equilibrium model are calculated using CALPHAD simulations. Differential scanning calorimeter is used to measure the heat flow during the solid-liquid phase transformation, the result of which is further converted to solidified fractions. The analytical model is compared with all the other models for validation.
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.