Ingenieurwissenschaften und zugeordnete Tätigkeiten
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The elastic properties (Young's modulus, shear modulus) of Ni-based alloy Inconel IN718 were investigated between room temperature and 800 °C in an additively manufactured variant (laser powder bed fusion, PBF‑LB/M) and from a conventional process route (hot rolled bar). The moduli were determined using the dynamic resonance method. The data set includes information on processing parameters, heat treatments, grain size, specimen dimensions and weight, Young’s and shear modulus as well as their measurement uncertainty.
The dataset was generated in an accredited testing lab using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data.
The elastic properties (Young's modulus, shear modulus) of austenitic stainless steel AISI 316L were investigated between room temperature and 900 °C in an additively manufactured variant (laser powder bed fusion, PBF‑LB/M) and from a conventional process route (hot rolled sheet). The moduli were determined using the dynamic resonance method. The data set includes information on processing parameters, heat treatments, grain size, specimen dimensions and weight, Young’s and shear modulus as well as their measurement uncertainty.
The dataset was generated in an accredited testing lab using calibrated measuring equipment. The calibrations meet the requirements of the test procedure and are metrologically traceable. The dataset was audited as BAM reference data.
This article reports temperature-dependent elastic properties (Young’s modulus, shear modulus) of three alloys measured by the dynamic resonance method. The alloys Ti-6Al-4V, Inconel IN718, and AISI 316 L were each investigated in a variant produced by an additive manufacturing processing route and by a conventional manufacturing processing route. The datasets include information on processing routes and parameters, heat treatments, grain size, specimen dimensions, and weight, as well as Young’s and shear modulus along with their measurement uncertainty. The process routes and methods are described in detail. The datasets were generated in an accredited testing lab, audited as BAM reference data, and are hosted in the open data repository Zenodo. Possible data usages include the verification of the correctness of the test setup via Young’s modulus comparison in low-cycle fatigue (LCF) or thermo-mechanical fatigue (TMF) testing campaigns, the design auf VHCF specimens and the use as input data for simulation purposes.
Additive manufacturing (AM) has revolutionized the manufacturing industry, offering a new paradigm to produce complex geometries and parts with customized properties. Among the different AM techniques, the wire arc additive manufacturing (WAAM) process has gained significant attention due to its high deposition rate and low equipment cost. However, the process is characterized by a complex thermal history, dynamic metallurgy, and mechanical behaviour that make it challenging to simulate it in real-time for online process control and optimization.
In this context, a reduced order model (ROM) using the proper generalized decomposition (PGD) method is proposed as a powerful tool to overcome the limitations of conventional numerical methods and enable the real-time simulation of the temperature field of WAAM processes. Though, the simulation of a moving heat source leads to a hardly separable parametric problem, which is handled by applying a novel mapping approach. Using this procedure, it is possible to create a simple separated representation of the model, also allowing to simulate multiple layers.
In this contribution, a PGD model is derived for the WAAM procedure simulating the temperature field. A good agreement with a standard finite element method is shown. The reduced model is further used in a stochastic model parameter estimation using Bayesian inference, speeding up calibrations and ultimately leading to a calibrated real-time simulation.
The microstructure has a great influence on short fatigue crack growth in metallic materials. Laser-based Powder Bed Fusion AlSi10Mg alloys exhibit in the as-built condition a fine fibrous Si structure and a supersaturated solid solution of Si in the α-Al matrix, which is significantly modified by heat treatments starting already at temperatures under 260 °C. This study focuses on the influence of post-process heat treatments on the microstructural evolution and the resulting fatigue crack growth resistance. As compared to the as-built condition, two heat treatments at 265 °C/1 h and at 300 °C/2 h are found to be beneficial to the fatigue crack growth resistance of the investigated material.
Additive manufacturing (AM) in general and laser powder bed fusion (PBF-LB/M) in particular are becoming increasingly important in the field of production technologies. Especially the high achievable accuracies and the great freedom in design make PBF-LB/M interesting for the manufacturing and repair of gas turbine blades. Part repair involves building AM-geometries onto an existing component. To minimise the offset between component and AM-geometry, a precise knowledge of the position of the component in the PBF-LB/M machine is mandatory. However, components cannot be inserted into the PBF-LB/M machine with repeatable accuracy, so the actual position will differ for each part. For an offset-free build-up, the actual position of the component in the PBF-LB/M machine has to be determined. In this paper, a camera-based position detection system is developed considering PBF-LB/M constraints and system requirements. This includes finding an optimal camera position considering the spatial limitations of the PBF-LB/M machine and analysing the resulting process coordinate systems. In addition, a workflow is developed to align different coordinate systems and simultaneously correct the perspective distortion in the acquired camera images. Thus, position characteristics can be determined from images by image moments. For this purpose, different image segmentation algorithms are compared. The precision of the system developed is evaluated in tests with 2D objects. A precision of up to 30μm in translational direction and an angular precision of 0.021∘ is achieved. Finally, a 3D demonstrator was built using this proposed hybrid strategy. The offset between base component and AM-geometry is determined by 3D scanning and is 69μm.
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.
Additive manufacturing (AM) processes such as laser powder bed fusion (PBF-LB/M) are rapidly gaining popularity in repair applications. Gas turbine components benefit from the hybrid repair process as only damaged areas are removed using conventional machining and rebuilt using an AM process. However, hybrid repair is associated with several challenges such as component fixation and precise geometry detection. This article introduces a novel fixturing system, including a sealing concept to prevent powder sag during the repair process. Furthermore, a high-resolution camera within an industrial PBF-LB/M machine is installed and used for object detection and laser recognition. Herein, process related inaccuracies such as PBF-LB/M laser drift is considered by detection of reference objects. This development is demonstrated by the repair of a representative gas turbine blade. The final offset between AM build-up and component is analysed. An approximate accuracy of 160 μm is achieved with the current setup.
Additive manufacturing (AM) processes such as laser powder bed fusion (PBF-LB/M) are rapidly gaining popularity in repair applications. Gas turbine components benefit from the hybrid repair process as only damaged areas are removed using conventional machining and rebuilt using an AM process. However, hybrid repair is associated with several challenges such as component fixation and precise geometry detection. This article introduces a novel fixturing system, including a sealing concept to prevent powder sag during the repair process. Furthermore, a high-resolution camera within an industrial PBF-LB/M machine is installed and used for object detection and laser recognition. Herein, process related inaccuracies such as PBF-LB/M laser drift is considered by detection of reference objects. This development is demonstrated by the repair of a representative gas turbine blade. The final offset between AM build-up and component is analysed. An approximate accuracy of 160 μm is achieved with the current setup.
Nickel alloys are cost intensive materials and generally classified as difficult-to-cut material. However, machining of these materials is needed especially in case of alloy 36 (1.3912), which is commonly used in mould construction for the production of fibre-reinforced composites. With regard to repair, modification and manufacturing of such components, additive manufacturing offers significant economic advantages. Nevertheless, subsequent machining steps are needed to achieve the final component contour and defined surface conditions. Dependent on the material and machining process conditions, detrimental tensile residual stresses may be the result on the machined surface, having negative impact on the component performance and safety. In this investigation, machining experiments were carried out on wire arc additive manufactured components made of alloy 36, varying the cutting speed and the feed rate. In addition, the conventional milling process (CM) was compared with a modern, hybrid machining process, the ultrasonic-assisted milling (US). The cutting forces and the surface-near residual stresses were analysed using X-ray diffraction. A significant improvement of the machinability as well as the surface integrity by using the ultrasonic assistance was observed, especially at low cutting speeds. The CM induced mainly tensile residual stresses, the US mainly compressive residual stresses.