Now showing 1 - 10 of 2618
  • Publication
    Result quality evaluation of Directed Energy Deposition Additive Manufacturing simulations with progressive simplification of transient heat-source motion
    ( 2022-09-05) ;
    Elsner, Beatrix A.M.
    ;
    Neubauer, Ingo
    ;
    ;
    Directed Energy Deposition (DED) additive manufacturing has recently been adopted in the industry for the build-up of structural components with weld lengths up to kilometers. As with all welding processes, DED suffers from thermal distortion, causing loss of dimensional accuracy and risk of cracking. Currently, process optimization with objective to minimize distortion requires expensive experimental trial-and-error. With numerical simulation of the DED process, this distortion compensation can be performed virtually, significantly reducing experimental trials. Although such approaches are generally available, their widespread adoption is currently being hampered by long computational times for large builds. This work presents a novel approach to reduce the calculation time by a simplification of the transient heat-source motion. This approach is assessed in terms of result accuracy for an industrial-scale component by progressively reducing the resolution of the heat-source motion. Calculation times as well as distortions in comparison to experimental trials are investigated.
  • Publication
    Laserstrahlhybridschweißen von Türmen für Windkraftanlagen
    ( 2022-08-29)
    Üstündag, Ömer
    ;
    Bakir, Nasim
    ;
    ;
    Knöfel, Frieder
    ;
    ; ;
    Das Laserstrahlhybridschweißen ist beim Schweißen von Türmen für Windkraftanlagen eine Alternative zum Unterpulverschweißen von Dickblechen in Mehrlagentechnik und bietet hier ökonomische und ökologische Vorteile. Der industrielle Einsatz des Verfahrens ist jedoch durch prozessspezifische Herausforderungen eingeschränkt. Die im Beitrag beschriebene kontaktlose elektromagnetische Badstütze dient zur Erweiterung des Verfahrenspotenzials im Dickblechbereich >15 mm.
  • Publication
    Integrated weld preparation designs for the joining of L-PBF and conventional components via TIG welding
    ( 2022-04-18)
    Geisen, Ole
    ;
    ;
    Graf, Benjamin
    ;
    Laser powder bed fusion (L-PBF) of entire assemblies is not typically practical for technical and economic reasons. The build size limitations and high production costs of L-PBF make it competitive for smaller, highly complex components, while the less complex elements of an assembly are manufactured conventionally. This leads to scenarios that use L-PBF only where it's beneficial, and it require an integration and joining to form the final product. For example, L-PBF combustion swirlers are welded onto cast parts to produce combustion systems for stationary gas turbines. Today, the welding process requires complex welding fixtures and tack welds to ensure the correct alignment and positioning of the parts for repeatable weld results. In this paper, L-PBF and milled weld preparations are presented as a way to simplify the Tungsten inert gas (TIG) welding of rotationally symmetrical geometries using integrated features for alignment and fixation. Pipe specimens with the proposed designs are manufactured in Inconel 625 using L-PBF and milling. The pipe assembly is tested and TIG welding is performed for validation. 3D scans of the pipes before and after welding are evaluated, and the weld quality is examined via metallography and computed tomography (CT) scans. All welds produced in this study passed the highest evaluation group B according to DIN 5817. Thanks to good component alignment, safe handling, and a stable welding process, the developed designs eliminate the need for part-specific fixtures, simplify the process chain, and increase the process reliability. The results are applicable to a wide range of components with similar requirements.
  • Publication
    Quality Prediction in Directed Energy Deposition Using Artificial Neural Networks Based on Process Signals
    ( 2022-04-14)
    Marko, Angelina
    ;
    Bähring, Stefan
    ;
    Raute, Maximilian Julius
    ;
    ;
    The Directed Energy Deposition process is used in a wide range of applications including the repair, coating or modification of existing structures and the additive manufacturing of individual parts. As the process is frequently applied in the aerospace industry, the requirements for quality assurance are extremely high. Therefore, more and more sensor systems are being implemented for process monitoring. To evaluate the generated data, suitable methods must be developed. A solution, in this context, was the application of artificial neural networks (ANNs). This article demonstrates how measurement data can be used as input data for ANNs. The measurement data were generated using a pyrometer, an emission spectrometer, a camera (Charge-Coupled Device) and a laser scanner. First, a concept for the extraction of relevant features from dynamic measurement data series was presented. The developed method was then applied to generate a data set for the quality prediction of various geometries, including weld beads, coatings and cubes. The results were compared to ANNs trained with process parameters such as laser power, scan speed and powder mass flow. It was shown that the use of measurement data provides additional value. Neural networks trained with measurement data achieve significantly higher prediction accuracy, especially for more complex geometries.
  • Publication
    Learning Demonstrator for Anomaly Detection in Distributed Energy Generation
    ( 2022-04-07)
    Pelchen, Timo
    ;
    Thiele, Gregor
    ;
    ;
    Radke, Marcel
    ;
    Schade, David
    ;
    Machine learning based anomaly detection methods on process data can be used to secure critical infrastructure. The design and installation of these methods require detailed understanding of both the facilities and the machine learning methods. Therefore, they are mostly incomprehensible for non-experts and thus acting as a barrier hindering the fast spread of such technologies. This article presents the systematic development of a demonstrator which enables presentations of anomaly detection on the example of a simulated wind farm. The specially designed user-interface allows a comprehensive experience. This article documents the use of the demonstrator for experts experienced in energy systems which are interested in the application of machine learning algorithms.
  • Publication
    Study on the transition behavior of the bulging effect during deep penetration laser beam welding
    ( 2022)
    Artinov, A.
    ;
    Meng, X.
    ;
    Bachmann, M.
    ;
    Rethmeier, M.
    The present work is devoted to the study of the transition behavior of the recently confirmed widening of the weld pool, known as the bulging effect, during high-power deep penetration laser beam welding of thick unalloyed steel sheets. A three-dimensional transient multi-physics numerical model is developed, allowing for the prediction of the bulge formation and the study of its temporal behavior. The model is generalized to account automatically for the transition from partial to complete penetration. Several experimental measurements and observations, such as drilling period, weld pool length, temperature, efficiency, and metallographic cross-sections are used to verify the model and assure the plausibility of the numerical results. The analysis of the calculated temperature and velocity distributions, as well as the evolution of the keyhole geometry, show that the formation of a bulging region strongly depends on the penetration depth of the weld. Based on the numerical results, the bulge is found to occur transiently, having its transition from a slight bulge to a fully developed bulging between penetration depths of 6 mm and 9 mm, respectively.
  • Publication
    Hybrid laser-arc welding of laser- and plasma-cut 20-mm-thick structural steels
    ( 2022)
    Üstündag, Ömer
    ;
    Bakir, Nasim
    ;
    ; ;
    It is already known that the laser beam welding (LBW) or hybrid laser-arc welding (HLAW) processes are sensitive to manufacturing tolerances such as gaps and misalignment of the edges, especially at welding of thick-walled steels due to its narrow beam diameter. Therefore, the joining parts preferably have to be milled. The study deals with the influence of the edge quality, the gap and the misalignment of edges on the weld seam quality of hybrid laser-arc welded 20-mm-thick structural steel plates which were prepared by laser and plasma cutting. Single-pass welds were conducted in butt joint configuration. An AC magnet was used as a contactless backing. It was positioned under the workpiece during the welding process to prevent sagging. The profile of the edges and the gap between the workpieces were measured before welding by a profile scanner or a digital camera, respectively. With a laser beam power of just 13.7 kW, the single-pass welds could be performed. A gap bridgeability up to 1 mm at laser-cut and 2 mm at plasma-cut samples could be reached respectively. Furthermore, a misalignment of the edges up to 2 mm could be welded in a single pass. The new findings may eliminate the need for cost and time-consuming preparation of the edges.
  • Publication
    Multiple-Wire Submerged Arc Welding of High-Strength Fine-Grained Steels
    ( 2022)
    Gook, S.
    ;
    ; ; ;
    Lichtenthäler, F.
    ;
    Stark, M.
    Ensuring the required mechanical-technological properties of welds is a critical issue in the application of multi-wire submerged arc welding process for welding high-strength fine-grained steels. Excessive heat input is one of the main causes for microstructural zones with deteriorated mechanical properties of the welded joint, such as a reduced notched impact strength and a lower structural robustness. A process variant is proposed which reduces the weld volume as well as the heat input by adjusting the welding wire configuration as well as the energetic parameters of the arcs, while retaining the advantages of multi-wire submerged arc welding such as high process stability and production speed.
  • Publication
    In situ microstructure analysis of Inconel 625 during laser powder bed fusion
    ( 2022)
    Schmeiser, F.
    ;
    Krohmer, E.
    ;
    Wagner, C.
    ;
    Schell, N.
    ;
    Uhlmann, E.
    ;
    Reimers, W.
    Laser powder bed fusion is an additive manufacturing process that employs highly focused laser radiation for selective melting of a metal powder bed. This process entails a complex heat flow and thermal management that results in characteristic, often highly textured microstructures, which lead to mechanical anisotropy. In this study, high-energy X-ray diffraction experiments were carried out to illuminate the formation and evolution of microstructural features during LPBF. The nickel-base alloy Inconel 625 was used for in situ experiments using a custom LPBF system designed for these investigations. The diffraction patterns yielded results regarding texture, lattice defects, recrystallization, and chemical segregation. A combination of high laser power and scanning speed results in a strong preferred crystallographic orientation, while low laser power and scanning speed showed no clear texture. The observation of a constant gauge volume revealed solid-state texture changes without remelting. They were related to in situ recrystallization processes caused by the repeated laser scanning. After recrystallization, the formation and growth of segregations were deduced from an increasing diffraction peak asymmetry and confirmed by ex situ scanning transmission electron microscopy.
  • Publication
    Methodology for a reverse engineering process chain with focus on customized segmentation and iterative closest point algorithms
    ( 2022) ;
    Schröder, Robert
    ;
    Stark, Rainer
    One-off construction is characterized by a multiplicity of manual manufacturing processes whereby it is based on consistent use of digital models. Since the actual state of construction does not match the digital models without manually updating them, the authors propose a method to automatically detect deviations and reposition the model data according to reality. The first essential method is based on the ""Segmentation of Unorganized Points and Recognition of Simple Algebraic Surfaces"" presented by Vanco et al.. The second method is the customization of the iterative closest point (ICP) algorithm. The authors present the overall structure of the implemented software, based on open source and relate it to the general reverse engineering (RE) framework by Buonamici et al.. A highlight will be given on: the general architecture of the software prototype; a customized segmentation and clustering of unorganized points and recognition of simple algebraic surfaces; the deviation analysis with a customized iterative closest point (CICP) algorithm Especially in the field of one-off construction, characterized by small and medium companies, automated assessment of 3D scan data during the design process is still in its infancy. By using an open source environment progress for consistent use of digital models could be accelerated.