TY - JOUR A1 - Bachmann, Marcel A1 - Putra, Stephen Nugraha A1 - Yang, Fan A1 - Meng, Xiangmeng A1 - Pusbatzkies, Pablo A1 - Rethmeier, Michael T1 - Elucidation of the laser beam energy attenuation by the vapor plume formation during high-power laser beam welding N2 - In high-power laser beam welding, a common phenomenon is the formation of a keyhole caused by the rapid evaporation of the material. Under atmospheric pressure, this evaporation generates a vapor plume that interacts with the laser beam, leading to energy attenuation and scattering of the laser radiation along its path. These interactions affect the stability of the process and the overall weld quality. This study investigates the influence of the vapor plume on the weld pool and keyhole dynamics during high-power laser beam welding of AlMg3 aluminum alloy through experimental and numerical approaches. The primary goal is to identify key vapor plume characteristics, particularly its length fluctuations, and to improve the accuracy of the numerical models. To achieve this, an algorithm was developed for the automated measurement of the vapor plume length using high-speed imaging and advanced data processing techniques. The measured plume length is then used to estimate additional vapor heating and laser energy attenuation using the Beer–Lambert law. A refined numerical CFD model, incorporating 3D transient heat transfer, fluid flow, and ray tracing, was developed to evaluate the vapor plume’s impact. Results show that already the time-averaged plume length effectively captures its transient influence and aligns well with experimental weld seam geometries. Additionally, energy scattering and absorption caused by the vapor plume led to a wider weld pool at the top surface. The study also shows an increased percentage of keyhole collapses due to the reduced laser power absorption at the keyhole bottom, further highlighting the importance of accurately modeling vapor plume effects. T2 - International Congress of Applications of Lasers & Electro-Optics 2025 CY - Orlando, USA DA - 12.10.2025 KW - Laser beam welding KW - Vapor plume formation KW - Weld pool KW - Keyhole dynamics KW - Numerical modeling PY - 2026 DO - https://doi.org/10.2351/7.0001863 SN - 1938-1387 IS - 38 SP - 012001-1 EP - 012001-9 PB - Laser Institute of America AN - OPUS4-64949 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - RPRT A1 - Bachmann, Marcel A1 - Rethmeier, Michael A1 - Meng, Xiangmeng T1 - Project title: Multi-physical simulation of the influence of an auxiliary magnetic field on the process porosity formation during high-power laser beam welding N2 - In this project, a multiphysically coupled numerical model will be developed to quantitatively describe porosity reduction in high-power laser beam welding of up to 10 mm thick AlMg3 using an oscillating magnetic field. The aim is to gain fundamental insights into the physical dependencies of the introduced electromagnetic forces on the melt pool behavior and the reduction of porosity. With the help of the numerical model, the transient, multi-coupled, three-dimensional problem of heat transfer, liquid flow, free surface deformation, and magnetic induction is to be solved, taking into account temperature-dependent material properties. The numerical modelling of the heat source will integrate all relevant physical mechanisms, for instance, multiple reflections of the laser radiation by an advanced ray tracing model, as well as local Fresnel absorption at the keyhole wall. This allows an analysis of the keyhole fluctuations, which have a dominant influence on the formation of process spores during deep penetration welding, based on physical principles. In addition, further physical factors such as the ablation pressure of the evaporating metal, the Laplace pressure, and Marangoni shear stresses are also to be integrated into the model. To evaluate the pore formation and reduction by means of the electromagnetic forces introduced in the molten pool, suitable models for describing the movement of the pores in the melt are to be developed. For the process pores, their movement can be implemented by tracking their surface under consideration of their internal pressure and temperature. With the help of the simulation model, all key factors for the formation of process pores during laser beam welding of the used aluminum alloy, as well as their avoidance, can be decoupled and analyzed. Accompanying welding tests are planned at BAM on a 20 kW fiber laser and a 16 kW disk laser. The magnetic flux density will be up to 500 mT at a maximum frequency of 5 kHz. The experimental results, in particular temperature measurements, weld cross sections, computer tomography, and X-ray examinations, will be used to verify the multiphysical model and its calibration. Moreover, the models will be validated and quantified by in situ high-speed imaging of the keyhole dynamics in a metal/quartz glass configuration with keyhole illumination by a diode laser coaxial to the processing laser. On the basis of the numerical and experimental results, the dependencies between applied magnetic field, melt pool behavior, and porosity formation will be revealed in this project. KW - Laser beam welding KW - Electromagnetic weld pool control KW - Numerical simulation KW - Process porosity PY - 2026 DO - https://doi.org/10.34657/27669 SP - 1 EP - 14 AN - OPUS4-65335 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 - Bachmann, Marcel A1 - Rethmeier, Michael T1 - Numerical studies of process porosity suppression by magnetohydrodynamic technology during the laser beam welding of aluminum alloy N2 - Magnetohydrodynamic (MHD) technology is acknowledged as a promising method for mitigating the porosity defects in laser-welded joints of aluminum alloys. A transient 3D multi-physical numerical model of laser beam welding (LBW), coupled with the MHD and oscillating metal vapor plume model, is developed to study the suppression mechanisms of process porosity by an external magnetic field. The experimental results demonstrate that the porosity ratio is reduced by 93.5 % as the oscillating magnetic field is applied. This significant reduction confirms the effectiveness of the MHD technology in suppressing porosity defects. A downward time-averaged Lorentz force is induced in the weld pool, which affects the fluid flow pattern and the weld pool profile. The change of the flowing pattern in the weld pool by the magnetic field does not always have a positive effect on the porosity suppression. In addition, an analytical model shows that the bubble escape window is expanded by 62 % under the effect of the oscillating magnetic field. The additional upward velocity provided by the electromagnetic expulsive force on the bubbles and the change of weld pool profile are considered favorable factors in eliminating the porosity defects. The numerical and analytical model developed for analyzing the bubble escape window have been validated by experimental results. KW - Laser beam welding KW - Aluminum alloy KW - Process porosity defects KW - Magnetohydrodynamic technology KW - Bubble escape KW - Numerical simulation PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-637642 DO - https://doi.org/10.1016/j.ijheatmasstransfer.2025.127525 SN - 0017-9310 VL - 253 SP - 1 EP - 13 PB - Elsevier Ltd. AN - OPUS4-63764 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Meng, Xiangmeng A1 - Bachmann, Marcel A1 - Yang, Fan A1 - Rethmeier, Michael T1 - Toward prediction and insight of porosity formation in laser welding: A physics-informed deep learning framework N2 - The laser welding process is an important manufacturing technology for metallic materials. However, its application is often hindered by the occurrence of porosity defects. By far, an accurate prediction of the porosity defects and an insight into its formation mechanism are still challenging due to the highly nonlinear physics involved. In this paper, we propose a physics-informed deep learning (PIDL) framework by utilizing mechanistic modeling and experimental data to predict the porosity level during laser beam welding of aluminum alloys. With a proper selection of the physical variables (features) concerning the solidification, liquid metal flow, keyhole stability, and weld pool geometry, the PIDL model shows great superiority in predicting the porosity ratio, with a reduction of mean square error by 41 %, in comparison with the conventional DL model trained with welding parameters. Furthermore, the selected variables are fused into dimensionless features with explicit physical meanings to improve the interpretability and extendibility of the PIDL model. Based on a well-trained PIDL model, the hierarchical importance of the physical variables/procedures on the porosity formation is for the first time revealed with the help of the Shapley Additive Explanations analysis. The keyhole ratio is identified as the most influential factor in the porosity formation, followed by the downward flow-driven drag force, which offers a valuable guideline for process optimization and porosity minimization. KW - Laser beam welding KW - Physics-informed deep learning KW - Porosity prediction KW - Feature fusion KW - Hierarchical importance PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-624708 DO - https://doi.org/10.1016/j.actamat.2025.120740 VL - 286 SP - 1 EP - 13 PB - Elsevier B.V. AN - OPUS4-62470 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Yang, Chunliang A1 - Yang, Fan A1 - Meng, Xiangmeng A1 - Putra, Stephen Nugraha A1 - Bachmann, Marcel A1 - Rethmeier, Michael T1 - Multi-refining effects of an AC electromagnetic field on the microstructure in AA5754 laser beam welding N2 - Fine-grain structure is beneficial to the mechanical properties of the joint. Different kinds of grain and sub-grain structures refined by magnetic field during laser beam welding of AA5754 aluminum alloy are analyzed in this manuscript, and the influences of different magnetic field parameters (magnetic flux density and frequency) in these refining effects are also studied. Using the scanning electron microscope (SEM), the sub-grain structure near the fusion line was obtained, and it was found that the branching promotion and branches refinement can be achieved by the magnetic field. The branches become finer with the magnetic flux density or frequency increases, and this effect is stronger in the dendritic region than in the equiaxed region. The results of electron backscatter diffraction (EBSD) in the equiaxed region show that a high-frequency magnetic field can greatly reduce the average grain size, while a low-frequency one has little effect. A phenomenological nucleation model based on dendrite fragmentation theory was established, and it was introduced into the phase field model to analyze the equiaxed grains evolution process. In addition, another refinement mechanism was also observed. The periodic solidification pattern caused by the unstable solidification in the molten pool can refine the grains, and the magnetic field promotes this kind of grain refinement by promoting the solidification period. KW - Laser beam welding KW - Magnetic field KW - Aluminum alloy KW - Crystal branch development KW - Periodic solidification pattern KW - Grain refinement PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-637222 DO - https://doi.org/10.1016/j.ijheatmasstransfer.2025.127509 SN - 0017-9310 VL - 252 SP - 1 EP - 16 PB - Elsevier Ltd. AN - OPUS4-63722 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Marquardt, Raphael A1 - Biegler, Max A1 - Rethmeier, Michael T1 - Influence of laser power on the melt pool shape of handheld laser beam welding of 1.5 mm thick micro alloyed steel N2 - Manual welding of structures requires highly skilled welders due to the large heat-affected zone of arc-based processes, that can negatively impact microstructure and cause distortion. Handheld laser beam welding is a promising alternative with high welding velocity and a concentrated heat input. However, its current use in industry is limited to parts with aesthetic requirements, often made of high-alloyed steel. To extend the use of handheld laser beam welding to low-cost steels with good mechanical properties, this study investigates the influence of laser power on the melt pool shape for micro-alloyed steel with a thickness of 1.5 mm. Tested joint geometries are T-joints welded with filler wire as well as butt joints and overlap joints without filler wire, which are typically found in assemblies under mechanical load. Weld quality is assessed by weld porosity analysis. The results show that the handheld laser beam welding with filler wire produces T-joints with a very good external appearance, but with porosity between level C and D in the cross sections according to DIN EN ISO 13919-1. By increasing the laser power, a deep penetration of the T-joint zone can be achieved without increasing the actual throat thickness. For handheld laser beam welding of butt joints a full penetration weld of the highest quality class can be reached. Overlap joints can be welded with full or partial penetration depending on the laser power selected, with quality classes between B and C in terms of porosity. T2 - 20th Nordic Laser Materials Processing Conference CY - Kongens Lyngby, Denmark DA - 26.08.2025 KW - Hand held laser welding KW - Laser beam welding KW - Low alloyed steel KW - Process parameter PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-641671 DO - https://doi.org/10.1088/1757-899X/1332/1/012015 SN - 1757-899X VL - 1332 SP - 1 EP - 6 PB - Institute of Physics CY - London [u.a.] AN - OPUS4-64167 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Savitsky, Viktor A1 - Schmies, Lennart A1 - Gumenyuk, Andrey A1 - Rethmeier, Michael T1 - Comparative performance of DIC and optical flow algorithms for displacement and strain analysis in laser beam welding N2 - The measurement of strain and displacement in the context of the welding process represents a significant challenge. Optical methods, such as digital image correlation (DIC) or optical flow algorithms, have demonstrated their efficacy in robust and reliable data acquisition in harsh environments, including those encountered in welding processes. Concurrently, a trade-off between the accuracy of the measurement and the computational resources required for the associated calculations must be evaluated on a case-by-case basis. The application of filters to initial images represents a technique that serves to enhance the quality and accuracy of the strain and displacement prediction. In the present study, the estimated error of two algorithms, namely the Lucas-Kanade (LK) and the inverse compositional Gauss-Newton (IC-GN), is compared on the basis of both synthetic and real welding images. The displacement field is evaluated for different zones in the laser weld seam with varying contrast performance. Based on the aforementioned results, a strain calculation was conducted for both methods, which yielded comparable results for the LK and IC-GN algorithms. KW - Laser speckle KW - DIC KW - Optical flow KW - Error estimation KW - Strain measurement KW - Laser beam welding PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-625919 DO - https://doi.org/10.1016/j.optlaseng.2025.108870 SN - 1873-0302 VL - 187 SP - 1 EP - 15 PB - Elsevier Ltd. AN - OPUS4-62591 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Huo, Wenjie A1 - Schmies, Lennart A1 - Gumenyuk, Andrey A1 - Rethmeier, Michael A1 - Wolter, Katinka T1 - Prediction of mean strain from laser beam welding images and detection of defects via strain curves based on machine learning N2 - With the advancement of machine learning, many predictions and measurements in visual tasks can be achieved by convolutional neural networks (CNNs). Solidification hot cracking is a significant defect in laser beam welding, commonly encountered in practical applications. Existing theories indicate that the formation of cracks is closely related to strain accumulation near the solidification front. In this paper, we first leverage supervised Regression networks to design CNNs that achieve real-time average strain estimation for each frame in the collected welding videos. Two different architectures are proposed and compared: the first model stacks two frames at a set interval and feeds them into the network, while the second model extracts image features individually and predicts the results by calculating the correlation between them. Each network has its own advantages in Terms of computational efficiency and accuracy. Finally, we further train a multilayer perceptron (MLP) classification model that can detect the occurrence of cracks based on the predicted strain behaviors. KW - Laser beam welding KW - Mean strain prediction KW - Solidification cracking detection Convolutional neural networks KW - Convolutional neural networks PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-644495 DO - https://doi.org/10.1016/j.optlastec.2025.113975 SN - 0030-3992 VL - 192, Part F SP - 1 EP - 8 PB - Elsevier Ltd. AN - OPUS4-64449 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bachmann, Marcel A1 - Putra, Stephen Nugraha A1 - Yang, Fan A1 - Meng, Xiangmeng A1 - Pusbatzkies, Pablo A1 - Rethmeier, Michael T1 - Elucidation of the Laser Beam Energy Attenuation by the Vapor Plume Formation during High Power Laser Beam Welding N2 - In high-power laser beam welding, a common phenomenon is the formation of a keyhole caused by the rapid evaporation of the material. Under atmospheric pressure, this evaporation generates a vapor plume that interacts with the laser beam, leading to energy attenuation and scattering of the laser radiation along its path. These interactions affect the stability of the process and the overall weld quality. This study investigates the influence of the vapor plume on the weld pool and keyhole dynamics during high-power laser beam welding of AlMg3 aluminum alloy through experimental and numerical approaches. The primary goal is to identify key vapor plume characteristics, particularly its length fluctuations, and to improve the accuracy of the numerical models. To achieve this, an algorithm was developed for the automated measurement of the vapor plume length using high-speed imaging and advanced data processing techniques. The measured plume length is then used to estimate the additional vapor heating and laser energy attenuation using the Beer–Lambert law. A refined numerical CFD model, incorporating 3D transient heat transfer, fluid flow, and ray tracing, was developed to evaluate the vapor plume’s impact. Results show that already the time-averaged plume length effectively captures its transient influence and aligns well with experimental weld seam geometries. Additionally, energy scattering and absorption caused by the vapor plume led to a wider weld pool at the top surface. The study also shows an increased percentage of keyhole collapses due to the reduced laser power absorption at the keyhole bottom, further highlighting the importance of accurately modeling vapor plume effects. T2 - International Congress of Applications of Lasers & Electro-Optics 2025 CY - Orlando, USA DA - 12.10.2025 KW - Laser beam welding KW - Vapor plume formation KW - Weld pool KW - Keyhole dynamics KW - Numerical modeling PY - 2025 SP - 1 EP - 10 AN - OPUS4-64817 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meng, Xiangmeng A1 - Bachmann, Marcel A1 - Kising, Pascal A1 - Yang, Fan A1 - Rethmeier, Michael T1 - Prediction of weld pool and keyhole geometries in high-power laser beam welding through a physics-informed generative artificial intelligence approach N2 - The weld pool and keyhole geometries are critical characteristics in evaluating the stability of the high-power laser beam welding (LBW) process and determining the resultant weld quality. However, obtaining these data through experimental or numerical methods remains challenging due to the difficulties in experimental measurements and the high computational demands of numerical modelling. This paper presents a physics-informed generative approach for predicting weld pool and keyhole geometries in the LBW process. With the help of a well experimentally validated numerical model considering the underlying physics in the LBW, the geometries of the weld pool and keyhole under various welding conditions are calculated, serving as the dataset of the generative model. A Conditional Variational Autoencoder (CVAE) model is employed to generate realistic 2D weld pool and keyhole geometries from the welding parameters. We utilize a β-VAE model with the Evidence Lower Bound (ELBO) loss function and include Kullback-Leibler divergence annealing to better optimize model performance and stability during training. The generated results show a good agreement with the ground truth from the numerical simulation. The proposed approach exhibits the potential of physics-informed generative models for a rapid and accurate prediction of the weld pool geometries across a diverse range of process parameters, offering a computationally efficient alternative to full numerical simulations for process optimization and control in laser beam welding processes. T2 - International Congress of Applications of Lasers & Electro-Optics 2025 CY - Orlando, USA DA - 12.10.2025 KW - Laser beam welding KW - Generative artificial intelligence KW - Machine learning KW - numerical simulation PY - 2025 SP - 1 EP - 10 AN - OPUS4-65075 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -