TY - JOUR A1 - Petrat, T. A1 - Kersting, R. A1 - Graf, B. A1 - Rethmeier, Michael T1 - Embedding electronics into additive manufactured components using laser metal deposition and selective laser melting N2 - The paper deals with the integration of a light emitting diode (LED) into an additive manufactured metal component. Selective laser melting (SLM) and laser metal deposition (LMD) are used. The material used is the chrome-nickel steel 316L. The basic component is manufactured by means of SLM and consists of a solid body and an area with grid structure. The solid body includes a duct in the shape of a groove with a recess for the positioning of the power cable. The LED is embedded in the grid structure via an inlet from the solid body. In further processing, the groove is filled with LMD. Two strategies with different parameter combinations were investigated. It shows that a high energy input near the power cable leads to its destruction. By using multiple parameter combinations during the manufacturing process, this destruction can be prevented. There was a comparison of both strategies with regard to the necessary number of tracks and duration of welding time. KW - Additive manufacturing KW - Condition monitoring KW - Process chain KW - Laser-metal-deposition KW - Selektive-laser-melting KW - Embedded electronics PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-479469 DO - https://doi.org/10.1016/j.procir.2018.08.071 SP - 168 EP - 171 PB - Elsevier Ltd. AN - OPUS4-47946 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 LME Susceptibility of Dual Phase Steel with Different Zinc Coatings N2 - The application of anti-corrosion coated, high-strength steels in the automotive industry has increased in recent years. In combination with various zinc-based surface coatings, liquid metal embrittlement cracking can be observed in some of these materials. A high-quality, crack-free spot-welded joint is essential to realize the lightweight potential of the materials. In this work, the LME susceptibility of different coatings, which will be determined by the crack length and the occurrence rate, will be investigated using a welding under external load setup. The uncoated specimens did not show any LME. EG, GI and GA showed significantly less LME than ZM coatings. The latter coatings showed much larger crack lengths than the EG, GI and GA coatings. Furthermore, two mechanisms regarding the LME occurrence rate were observed: the occurrence of LME in zinc–magnesium coatings was theorized to be driven by the material properties of the coatings, whereas the occurrence of LME at EG, GI and GA samples was forced mainly by the application of the external tensile load. In the experimental setup of this work, the materials were exposed to unusually high mechanical loads (up to 80% of their yield strength) to evoke LME cracks. KW - Widerstandspunktschweißen KW - Hochfester Stahl KW - Liquid Metal Embrittlement KW - Flüssigmetallinduzierte Rissbildung KW - Zink KW - AHSS PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-580428 DO - https://doi.org/10.3390/met13050890 VL - 13 IS - 5 SP - 1 EP - 11 PB - MDPI AN - OPUS4-58042 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ávila Calderón, Luis Alexander A1 - Graf, B. A1 - Rehmer, Birgit A1 - Petrat, T. A1 - Skrotzki, Birgit A1 - Rethmeier, Michael T1 - Characterization of Ti-6Al-4V fabricated by multilayer laser powder-based directed energy deposition N2 - Laser powder-based directed energy deposition (DED-L) is increasingly being used in additive manufacturing (AM). As AM technology, DED-L must consider specific challenges. It must achieve uniform volume growth over hundreds of layers and avoid heat buildup of the deposited material. Herein, Ti–6Al–4V is fabricated using an approach that addresses these challenges and is relevant in terms of transferability to DED–L applications in AM. The assessment of the obtained properties and the discussion of their relationship to the process conditions and resulting microstructure are presented. The quality of the manufacturing process is proven in terms of the reproducibility of properties between individual blanks and with respect to the building height. The characterization demonstrates that excellent mechanical properties are achieved at room temperature and at 400 °C. KW - AGIL KW - Laser powder-based directed energy deposition KW - Tensile properties KW - Ti-6Al-4V KW - Microstructure PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-542262 DO - https://doi.org/10.1002/adem.202101333 SN - 1438-1656 SN - 1527-2648 SP - 1 EP - 15 PB - Wiley-VCH CY - Weinheim AN - OPUS4-54226 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Strobl, Dominic A1 - Unger, Jörg F. A1 - Ghnatios, C. A1 - Klawoon, Alexander A1 - Pittner, Andreas A1 - Rethmeier, Michael A1 - Robens-Radermacher, Annika T1 - Efficient bead-on-plate weld model for parameter estimation towards effective wire arc additive manufacturing simulation N2 - 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. KW - Proper generalized decomposition KW - Model order reduction KW - Hardly separable problem KW - Additive manufacturing KW - Model calibration KW - Wire arc additive manufacturing PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-596502 DO - https://doi.org/10.1007/s40194-024-01700-0 SN - 0043-2288 SP - 1 EP - 18 PB - Springer AN - OPUS4-59650 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hartwig, Philipp A1 - Bakir, Nasim A1 - Gumenyuk, Andrey A1 - Scheunemann, Lisa A1 - Schröder, Jörg A1 - Rethmeier, Michael T1 - A Physically Motivated Heat Source Model for Laser Beam Welding N2 - In this contribution, we present a physically motivated heat source model for the numerical modeling of laser beam welding processes. Since the calibration of existing heat source models, such as the conic or Goldak model, is difficult, the representation of the heat source using so-called Lamé curves has been established, relying on prior Computational Fluid Dynamics (CFD) simulations. Lamé curves, which describe the melting isotherm, are used in a subsequent finite-element (FE) simulation to define a moving Dirichlet boundary condition, which prescribes a constant temperature in the melt pool. As an alternative to this approach, we developed a physically motivated heat source model, which prescribes the heat input as a body load directly. The new model also relies on prior CFD simulations to identify the melting isotherm. We demonstrate numerical results of the new heat source model on boundary-value problems from the field of laser beam welding and compare it with the prior CFD simulation and the results of the Lamé curve model and experimental data. KW - Welding simulation KW - Heat source models KW - Laser beam welding KW - Thermal analysis PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-600899 DO - https://doi.org/10.3390/met14040430 VL - 14 IS - 4 SP - 1 EP - 26 PB - MDPI CY - Basel AN - OPUS4-60089 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Yang, Fan A1 - Meng, Xiangmeng A1 - Putra, Stephen Nugraha A1 - Artinov, Antoni A1 - Bachmann, Marcel A1 - Rethmeier, Michael T1 - Numerical analysis of the effect of an oscillating metal vapor plume on the keyhole and molten pool behavior during deep penetration laser beam welding N2 - The effect of the oscillating metal vapor plume on the keyhole and molten pool behavior during the laser beam welding of AlMg3 aluminum alloys is investigated by experimental and numerical methods. The real-time height of the metal vapor plume is measured by high-speed camera observation. The obtained experimental results are used to evaluate the additional heating source and laser beam attenuation caused by the scattering and absorption based on the Beer–Lambert theory. Furthermore, the dynamic behavior of the metal vapor plume is incorporated into a 3D transient heat transfer and fluid flow model, coupled with the ray tracing method, for the laser beam welding of the AlMg3 alloy. It is found that additional heating resulting from the scattered and absorbed laser beam energy by the metal vapor plume significantly expands the shape of the molten pool on the top region. Moreover, the oscillating metal vapor plume caused the fluctuation of the high-temperature region in the molten pool. The probability of keyhole collapse at the bottom increases 17% due to the oscillating laser power induced by the laser beam attenuation. The internal interplay between the metal vapor plume, molten pool shape, and keyhole collapse is obtained. The developed model has been validated by experiments, which shows a good agreement. T2 - International Congress of Applications of Lasers & Electro-Optics 2023 CY - Chicago, IL, USA DA - 16.10.2023 KW - Deep penetration laser beam welding KW - Numerical simulation KW - Oscillating vapor plume KW - Keyhole collapse PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-587978 DO - https://doi.org/10.2351/7.0001094 SN - 1938-1387 SN - 1042-346X VL - 35 IS - 4 SP - 1 EP - 10 PB - AIP Publishing CY - Melville, NY AN - OPUS4-58797 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Huo, W. A1 - Bakir, Nasim A1 - Gumenyuk, Andrey A1 - Rethmeier, Michael A1 - Wolter, K. T1 - Strain Prediction Using Deep Learning during Solidification Crack Initiation and Growth in Laser Beam Welding of Thin Metal Sheets N2 - The strain field can reflect the initiation time of solidification cracks during the welding process. The traditional strain measurement is to first obtain the displacement field through digital image correlation (DIC) or optical flow and then calculate the strain field. The main disadvantage is that the calculation takes a long time, limiting its suitability to real-time applications. Recently, convolutional neural networks (CNNs) have made impressive achievements in computer vision. To build a good prediction model, the network structure and dataset are two key factors. In this paper, we first create the training and test sets containing welding cracks using the controlled tensile weldability (CTW) test and obtain the real strain fields through the Lucas–Kanade algorithm. Then, two new networks using ResNet and DenseNet as encoders are developed for strain prediction, called StrainNetR and StrainNetD. The results show that the average endpoint error (AEE) of the two networks on our test set is about 0.04, close to the real strain value. The computation time could be reduced to the millisecond level, which would greatly improve efficiency. KW - Convolutional neural network KW - Strain fields prediction KW - Laser beam welding KW - Solidification cracking PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-570565 DO - https://doi.org/10.3390/app13052930 VL - 13 IS - 5 SP - 1 EP - 15 PB - MDPI AN - OPUS4-57056 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Artinov, Antoni A1 - Karkhin, V. A1 - Meng, Xiangmeng A1 - Bachmann, Marcel A1 - Rethmeier, Michael T1 - A General Analytical Solution for Two-Dimensional Columnar Crystal Growth during Laser Beam Welding of Thin Steel Sheets N2 - A technique for calculating the main solidification parameters for a two-dimensional columnar crystal growth during complete penetration laser beam welding of thin steel sheets was developed. Given that the weld pool interface is described by Lamé curves (superellipses) within the horizontal plane of growth, general analytical solutions were derived for the geometry of the crystal axis and the corresponding growth rate and cross-sectional area of the crystal. A dimensionless analysis was performed to provide insights on the dependence of the solidification parameters on the shape and dimensions of the rear part of the weld pool boundary. The derived solutions were applied for the case of complete penetration laser beam keyhole welding of 2 mm thick 316L austenitic chromium-nickel steel sheets. It was shown that the reconstruction of the weld pool boundary with Lamé curves provides higher accuracy and flexibility compared to results obtained with elliptical functions. The validity of the proposed technique and the derived analytical solutions was backed up by a comparison of the obtained solutions to known analytical solutions and experimentally determined shapes and sizes of the crystals on the top surface of the sheet. The dimensions of the calculated crystal axis correlated well with the experimentally obtained results. KW - General analytical solutions KW - Two-dimensional solidification KW - Columnar crystal growth KW - Lamé curves KW - Laser beam welding PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-576788 DO - https://doi.org/10.3390/app13106249 IS - 10 SP - 1 EP - 10 ET - 13 AN - OPUS4-57678 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Gook, Sergej A1 - El-Batahgy, Abdel-Monem A1 - Gumenyuk, Andrey A1 - Biegler, Max A1 - Rethmeier, Michael T1 - Application of Hybrid Laser Arc Welding for Construction of LNG Tanks Made of Thick Cryogenic 9% Ni Steel Plates N2 - Hybrid laser-arc welding (HLAW) was applied for butt welding of 14.5 mm thick plates of ferritic cryogenic steel X8Ni9 containing 9% Ni, which is used for manufacturing storage and transport facilities of liquefied natural gas (LNG). The weld seam formation and the achievable metallurgical and mechanical properties of the hybrid welds were investigated experimentally for two types of filler wire, an austenitic wire dissimilar to the base metal (BM) and an experimentally produced matching ferritic wire. Safe penetration and uniform distribution of the austenitic filler metal in the narrow hybrid weld could only be achieved in the upper, arcdominated part of the weld. The pronounced heterogeneous distribution of the austenitic filler metal in the middle part and in the root area of the weld could not ensure sufficient notched impact toughness of the weld metal (WM). As a result, a decrease in the impact energy down to 17±3 J was observed, which is below the acceptance level of ≥34 J for cryogenic applications. In contrast, the use of a matching ferritic filler wire resulted in satisfactory impact energy of the hybrid welds of up to 134±52 J at the concerned cryogenic temperature of -196 °C. The obtained results contribute to an important and remarkable conversion in automated manufacturing of LNG facilities. In other words, the results will help to develop a new laser-based welding technology, where both quality and productivity are considered.The efficiency of the developed welding process has been demonstrated by manufacturing a prototype where a segment of the inner wall of large size LNG storage tank was constructed. In this concern, hybrid laser arc welding was conducted in both horizontal (2G) and vertical (3G) positions as a simulation to the actual onsite manufacturing. The prototype was fabricated twice where its quality was confirmed based on non-destructive and destructive examinations. KW - Hardness KW - Hybrid Laser arc Welding KW - 9% Ni Steel KW - Fusion zone size KW - Microstructure KW - Tensile Strength KW - Impact Absorbed Energy PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-586080 DO - https://doi.org/10.1007/s40516-023-00229-2 SP - 1 EP - 22 PB - Springer Nature AN - OPUS4-58608 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Huo, Wenjie A1 - Bakir, Nasim A1 - Gumenyuk, Andrey A1 - Rethmeier, Michael A1 - Wolter, Katinka T1 - Detection of solidification crack formation in laser beam welding videos of sheet metal using neural networks N2 - AbstractLaser beam welding has become widely applied in many industrial fields in recent years. Solidification cracks remain one of the most common welding faults that can prevent a safe welded joint. In civil engineering, convolutional neural networks (CNNs) have been successfully used to detect cracks in roads and buildings by analysing images of the constructed objects. These cracks are found in static objects, whereas the generation of a welding crack is a dynamic process. Detecting the formation of cracks as early as possible is greatly important to ensure high welding quality. In this study, two end-to-end models based on long short-term memory and three-dimensional convolutional networks (3D-CNN) are proposed for automatic crack formation detection. To achieve maximum accuracy with minimal computational complexity, we progressively modify the model to find the optimal structure. The controlled tensile weldability test is conducted to generate long videos used for training and testing. The performance of the proposed models is compared with the classical neural network ResNet-18, which has been proven to be a good transfer learning model for crack detection. The results show that our models can detect the start time of crack formation earlier, while ResNet-18 only detects cracks during the propagation stage. KW - Artificial Intelligence KW - Software PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-586116 DO - https://doi.org/10.1007/s00521-023-09004-y SN - 0941-0643 VL - 35 IS - 34 SP - 24315 EP - 24332 PB - Springer Science and Business Media LLC AN - OPUS4-58611 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -