TY - JOUR A1 - Üstündag, Ömer A1 - Bakir, Nasim A1 - Gook, S. A1 - Gumenyuk, Andrey A1 - Rethmeier, Michael T1 - Hybrid laser‑arc welding of laser‑ and plasma‑cut 20‑mm‑thick structural steels JF - Welding in the World 2022 N2 - 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. KW - Hybrid laser-arc welding KW - Thick-walled steel KW - Edge quality KW - Gap bridgeability KW - Laser cutting KW - Plasma cutting PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-552013 DO - https://doi.org/10.1007/s40194-022-01255-y SN - 0043-2288 VL - 66 SP - 507 EP - 514 PB - Springer AN - OPUS4-55201 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Meng, Xiangmeng A1 - Putra, Stephen Nugraha A1 - Bachmann, Marcel A1 - Artinov, Antoni A1 - Rethmeier, Michael T1 - Influence of the free surface reconstruction on the spatial laser energy distribution in high power laser beam welding modeling JF - Journal of Laser Applications N2 - An accurate and efficient description of the spatial distribution of laser energy is a crucial factor for the modeling of laser material processing, e.g., laser welding, laser cutting, or laser-based additive manufacturing. In this study, a 3D heat transfer and fluid flow model coupled with the volume-of-fluid algorithm for free surface tracking is developed for the simulation of molten pool dynamics in high-power laser beam welding. The underlying laser-material interactions, i.e., the multiple reflections and Fresnel absorption, are considered by a raytracing method. Two strategies of free surface reconstruction used in the ray-tracing method are investigated: a typical piecewise linear interface calculation (PLIC)-based method and a novel localized level-set method. The PLIC-based method is discrete, resulting in noncontinuous free surface reconstruction. In the localized level-set method, a continuous free surface is reconstructed, and, thus, the exact reflection points can be determined. The calculated spatial laser energy distribution and the corresponding molten pool dynamics from the two methods are analyzed and compared. The obtained numerical results are evaluated with experimental measurements to assure the validity of the proposed model. It is found that distinct patterns of the beam multiple reflections are obtained with the different free surface reconstructions, which shows significant influence not only on the molten pool behaviors but also on the localized keyhole dynamics. KW - Laser beam welding KW - Laser energy distribution KW - Weld pool dynamics KW - Ray teacing PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-562429 DO - https://doi.org/10.2351/7.0000739 SN - 1042-346X VL - 34 IS - 4 SP - 042023-1 EP - 042023-8 PB - Laser Institute of America CY - Orlando, Fla. AN - OPUS4-56242 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - El-Batahgy, A. A1 - Elkousy, M. A1 - Al-Rahman, A. A1 - Gumenyuk, Andrey A1 - Rethmeier, Michael A1 - Gook, S. T1 - Retaining Mechanical Properties of GMA-Welded Joints of 9%Ni Steel Using Experimentally Produced Matching Ferritic Filler Metal JF - materials N2 - Motivated by the loss of tensile strength in 9%Ni steel arc-welded joints performed using commercially available Ni-based austenitic filler metals, the viability of retaining tensile strength using an experimentally produced matching ferritic filler metal was confirmed. Compared to the austenitic Ni-based filler metal (685 MPa), higher tensile strength in gas metal arc (GMA) welded joints was achieved using a ferritic filler metal (749 MPa) due to its microstructure being similar to the base metal (645 MPa). The microstructure of hard martensite resulted in an impact energy of 71 J (-196 °C), which was two times higher than the specified minimum value of _>34 J. The tensile and impact strength of the welded joint is affected not only by its microstructure, but also by the degree of its mechanical mismatch depending on the type of filler metal. Welds with a harder microstructure and less mechanical mismatch are important for achieving an adequate combination of tensile strength and notched impact strength. This is achievable with the cost-effective ferritic filler metal. A more desirable combination of mechanical properties is guaranteed by applying low preheating temperature (200 °C), which is a more practicable and economical solution compared to the high post-weld heat treatment (PWHT) temperature (580 °C) suggested by other research. KW - 9%Ni steel KW - Ni-based austenitic filler metal KW - Mechanical mismatching KW - Microstructure KW - Post-weld heat treatment KW - Preheating KW - Matching ferritic filler metal PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-564610 DO - https://doi.org/10.3390/ma15238538 SN - 1996-1944 VL - 15 IS - 23 SP - 1 EP - 14 PB - MDPI AN - OPUS4-56461 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Üstündag, Ömer A1 - Bakir, Nasim A1 - Gumenyuk, Andrey A1 - Rethmeier, Michael T1 - Improvement of Charpy impact toughness by using an AC magnet backing system for laser hybrid welding of thick S690QL steels JF - Procedia CIRP N2 - The study deals with the influence of the heat input and the resulting cooling times on the microstructure and Charpy impact toughness of single-pass laser hybrid welded 20-mm thick high-strength steel S690QL. The main focus is on the change of the mechanical properties over the entire seam thickness. The cooling times were measured in-situ using a pyrometer and an optical fibre in three different depths of the seam where Charpy impact test specimens were also later taken. Thereby, three different heat inputs from 1.3 kJ/mm to 2 kJ/mm were investigated. Despite the observed decreased values of both t8/5-cooling time and the Charpy impact toughness in the root part of the seam, the required impact toughness of 38 J/cm2 could be reached in dependance on applied heat input, especially at the heat input of 1.6 kJ/mm. T2 - 12th CIRP conference on photonic technologies [lane 2022] CY - Fürth, Germany DA - 04.09.2022 KW - Thick-plate welding KW - Laser hybrid welding KW - Electromagnetic backing KW - Charpy impact toughness KW - Thermal cycles PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-563731 DO - https://doi.org/10.1016/j.procir.2022.08.067 VL - 111 SP - 462 EP - 465 PB - Elsevier B.V. AN - OPUS4-56373 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bakir, Nasim A1 - Üstündag, Ömer A1 - Gumenyuk, Andrey A1 - Rethmeier, Michael T1 - Influence of the weld pool geometry on solidification cracking in partial penetration high power laser beam welding JF - 12TH CIRP Conference on photonic technologies (LANE 2022) N2 - Solidification cracking is still a serious problem in laser beam welding, especially in the welding of thick-walled plates. The influence of weld pool geometry on solidification cracking in partial penetration welding of thick plates is investigated within scope of this study. Therefore, a specific experimental setup of steel and quartz glass in butt configuration and on the side with high-speed camera were used to record the weld pool shape. In addition, the influence of laser inclination angle on the weld pool geometry and on solidification crack formation was investigated. The results show a bulge in the weld pool root, which is separated from an upper region by a necking region. This leads to a case where there are three different longitudinal region lengths with different solidification zones. This temporal sequence of solidification strongly promotes the formation of solidification cracks in the weld root. T2 - 12th CIRP Conference on photonic technologies (LANE 2022) CY - Fürth, Germany DA - 04.09.2022 KW - Laser beam welding KW - Partial penetration KW - Weld pool shape PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-563940 DO - https://doi.org/10.1016/j.procir.2022.08.174 VL - 111 SP - 397 EP - 400 PB - Elsevier B.V. AN - OPUS4-56394 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Artinov, Antoni A1 - Meng, Xiangmeng A1 - Bachmann, Marcel A1 - Rethmeier, Michael T1 - Study on the transition behavior of the bulging effect during deep penetration laser beam welding JF - International Journal of Heat and Mass Transfer N2 - 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, shows 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. KW - Laser beam welding KW - Deep penetration KW - Bulge formation KW - Numerical modeling PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-545067 DO - https://doi.org/10.1016/j.ijheatmasstransfer.2021.122171 VL - 184 SP - 122171 PB - Elsevier Ltd. AN - OPUS4-54506 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Straße, Anne A1 - Gumenyuk, Andrey A1 - Rethmeier, Michael T1 - Study on Duplex Stainless Steel Powder Compositions for the Coating of thick Plates of Laser Beam Welding JF - Advanced Engineering Materials N2 - Duplex stainless steels combine the positive properties of its two phases, austenite and ferrite. Due to its good corrosion resistance, high tensile strength, and good ductility, it has multiple applications. But laser beam welding of duplex steels changes the balanced phase distribution in favor of ferrite. This results in a higher vulnerability to corrosion and a lower ductility. Herein, different powder combinations consisting of duplex and nickel for coating layers by laser metal deposition (LMD) are investigated. Afterward, laser tracks are welded, and the temperature cycles are measured. The ferrite content of the tracks is analyzed by feritscope, metallographic analysis, and electron backscatter diffraction. The goal is the development of a powder mixture allowing for a duplex microstructure in a two-step process, where first the edges of the weld partners are coated with the powder mixture by LMD and second those edges are laser beam welded. The powder mixture identified by the pretests is tested in the two-step process and analyzed by metallographic analysis, energy-dispersive X-ray spectroscopy, and Vickers hardness tests. The resulting weld seams show a balanced duplex microstructure with a homogenous nickel distribution and a hardness of the weld seam similar to the base material. KW - Duplex AISI 2205 KW - Laser metal deposition KW - Laser beam welding KW - Nickel KW - Stainless steels PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-547024 DO - https://doi.org/10.1002/adem.202101327 SN - 1438-1656 SP - 1 EP - 11 PB - Wiley-VCH CY - Weinheim AN - OPUS4-54702 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Marko, A. A1 - Bähring, S. A1 - Raute, J. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Quality Prediction in Directed Energy Deposition Using Artificial Neural Networks Based on Process Signals JF - Applied Sciences N2 - 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. KW - DED KW - Artificial neural network KW - Process monitoring KW - Quality assurance KW - Data preparation PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-547039 DO - https://doi.org/10.3390/app12083955 VL - 12 IS - 8 SP - 1 EP - 13 PB - MDPI AN - OPUS4-54703 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Geisen, O. A1 - Müller, V. A1 - Graf, B. A1 - Rethmeier, Michael T1 - Integrated weld preparation designs for the joining of L‑PBF and conventional components via TIG welding JF - Progress in Additive Manufacturing N2 - 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. KW - L-PBF KW - AM feature integration KW - TIG welding KW - Integrated alignment features KW - Pipe weld preparation KW - Dissimilar joints KW - Inconel 625 PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-547042 DO - https://doi.org/10.1007/s40964-021-00221-2 SN - 2363-9512 SP - 1 EP - 11 PB - Springer AN - OPUS4-54704 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - El-Sari, B. A1 - Biegler, M. A1 - Rethmeier, Michael T1 - Investigation of the Extrapolation Capability of an Artificial Neural Network Algorithm in Combination with Process Signals in Resistance Spot Welding of Advanced High-Strength Steels JF - Metals N2 - Resistance spot welding is an established joining process for the production of safetyrelevant components in the automotive industry. Therefore, consecutive process monitoring is essential to meet the high quality requirements. Artificial neural networks can be used to evaluate the process parameters and signals, to ensure individual spot weld quality. The predictive accuracy of such algorithms depends on the provided training data set, and the prediction of untrained data is challenging. The aim of this paper was to investigate the extrapolation capability of a multi-layer perceptron model. That means, the predictive performance of the model was tested with data that clearly differed from the training data in terms of material and coating composition. Therefore, three multi-layer perceptron regression models were implemented to predict the nugget diameter from process data. The three models were able to predict the training datasets very well. The models, which were provided with features from the dynamic resistance curve predicted the new dataset better than the model with only process parameters. This study shows the beneficial influence of process signals on the predictive accuracy and robustness of artificial neural network algorithms. Especially, when predicting a data set from outside of the training space. KW - Automotive KW - Artificial intelligence KW - Quality monitoring KW - Resistance spot welding KW - Quality assurance PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-539783 DO - https://doi.org/10.3390/met11111874 VL - 11 IS - 11 SP - 1 EP - 11 PB - MDPI AN - OPUS4-53978 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -