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A fundamental study of physical mechanisms of wineglass-shaped fusion zone profile in laser melting
(2024)
The fusion zone geometry in laser melting processes e.g., laser welding and laser-based additive manufacturing, of metallic materials has commonly a wineglass-shaped profile which is critical to the grain orientation and stress distribution. Hereby, we adopt for the first time a decoupling work through a combination of multi-physics modelling and experiments to reveal the fundamental mechanisms of this special morphology. Two physicsbased easy-to-use metal vapour models are proposed to consider the vapour’s momentum and thermal effects separately. It is found that the direct laser energy absorption and Marangoni shear stress which are widely hypothesised to dominate the wineglass-shape formation show only a minor influence. The additional heating from the metallic vapour plume rather than its momentum impact contributes predominantly to the enlarging of the molten pool top region, resulting directly in the formation of the wineglass-shaped fusion zone. The generality of the plume heating effect is also validated in two types of materials (steel and Al) in a wide range of parameters.
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.
Numerical and experimental assessment of liquid metal embrittlement in externally loaded spot welds
(2024)
Zinc-based surface coatings are widely applied with high-strength steels in automotive industry. Some of these base materials show an increased brittle cracking risk during loading. It is necessary to examine electrogalvanized and uncoated samples of a high strength steel susceptible to liquid metal embrittlement during spot welding with applied external load. Therefore, a newly developed tensile test method with a simultaneously applied spot weld is conducted. A fully coupled 3D electrical, thermal, metallurgical and mechanical finite element model depicting the resistant spot welding process combined with the tensile test conducted is mandatory to correct geometric influences of the sample geometry and provides insights into the sample’s time dependent local loading. With increasing external loads, the morphology of the brittle cracks formed is affected more than the crack depth. The validated finite element model applies newly developed damage indicators to predict and explain the liquid metal embrittlement cracking onset and development as well as even ductile failure.
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.
The spatial laser energy absorption inside the keyhole is decisive for the dynamic molten pool behaviors and the resultant weld properties in high-power laser beam welding (LBW). In this paper, a numerical simulation of the LBW process, considering the 3D transient heat transfer, fluid flow, and keyhole dynamics, is implemented, in which the free surface is tracked by the volume-of-fluid algorithm. The underlying laser-material interactions, i.e., the multiple reflections and Fresnel absorption, are considered by an advanced ray-tracing method based on a localized level-set strategy and a temperature-dependent absorption coefficient. The laser energy absorption is analyzed from a time-averaged point of view for a better statistical representation. It is found for the first time that a significant drop in the time-averaged laser energy absorption occurs at the focus position of the laser beam and that the rest of the keyhole region has relatively homogeneous absorbed energy. This unique absorption pattern may lead to a certain keyhole instability and have a strong correlation with the detrimental bulging and narrowing phenomena in the molten pool. The influence of different focus positions of the laser beam on the keyhole dynamics and molten pool profile is also analyzed. The obtained numerical results are compared with experimental measurements to ensure the validity of the proposed model.
Liquid metal embrittlement (LME) cracking is a phenomenon observed during resistance spot welding (RSW) of zinccoated advanced highstrength steels (AHSS) in automotive manufacturing. In this study, severe cracks are observed at the edge of the sheet under reduced flange widths. These cracks, traversing the AHSS sheet, culminate at the edge with a width of approximately 1.2 mm.
Through combined numerical and experimental investigations, and material testing, these cracks are identified and validated as a new type of LME crack. The mechanism behind this crack formation is attributed to unique geometric conditions that, when compared to center welding, amplify radial material flow by ninefold to 0.87 mm. The resultant tangential tensile stresses approximate 760 MPa, which exceed the yield strength of the examined advanced highstrength steel (AHSS) under heightened temperature conditions, and when combined with liquid zinc, promote the formation of this new type of LME crack.
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.
Through experimental observation and auxiliary numerical simulation, this investigation studies the different types of grain refinement of 5754 aluminum alloy laser beam welding by applying a transverse oscillating magnetic field. Scanning electron microscope results have proved that the application of a magnetic field can reduce the average crystal branch width and increase its number. The interaction between the induced eddy current generated by the Seebeck effect and the applied external magnetic field produces a Lorentz force, which is important for the increase in the number of crystal branches. Based on the theory of dendrite fragmentation and the magnetic field-induced branches increment, the grain size reduction caused by the magnetic field is studied. Furthermore, the effects of the magnetic field are analyzed by combining a phase field method model and simulations of nucleation and grain growth. The grain distribution and average grain
size after welding verify the reliability of the model. In addition, the introduction of a magnetic field can increase the number of periodic three-dimensional solidification patterns. In the intersection of two periods of solidification patterns, the metal can be re-melted and then re-solidified, which prevents the grains, that have been solidified and formed previously, from further growth and generates some small cellular grains in the new fusion line. The magnetic field increases the building frequency of these solidification structures and thus promotes this kind of grain refinement.
Electromagnetic stirring is known to promote material flow, reduce porosity, uniform elements distribution, and refine grain in laser beam welding (LBW), which enhances the applicability of LBW in various industries. In this study, a phase-field model of dendrite growth in AA5754 Al alloy electromagnetic stirring laser beam welding was established. The model considered the thermal electromagnetic Lorentz force resulting from the interaction between the electric field generated by the Seebeck effect and the magnetic field, as well as the temperature gradient and solidification rate of the solidification interface obtained from the computational fluid dynamics electromagnetic stirring LBW model. The variation rules of dendrite growth with different magnetic parameters and effects are analyzed. Comprehensively, the magnetic field promotes the solidification rate, thus promoting interfacial instability and a large magnetic flux density leads to a faster interface instability. The solidification rate as well as the temperature gradient affect the growth rate, and the accelerated growth caused by the so lidification rate with a high frequency and a large magnetic flux density effectively inhibits the slow growth caused by the temperature gradient. The thermal electromagnetic Lorentz force is the main factor for the branch increment at low frequencies, while both thermal electromagnetic Lorentz force and temperature gradient in crease the number of branches at high frequencies. The calculated average branch numbers considering various factors in the stable stage under different magnetic parameters were consistent with the results of the scanning electron microscope tests.
The amount of absorbed energy in the keyhole as well as its spatial and temporal distribution is essential to model the laser beam welding process. The recoil pressure, which develops because of the evaporation process induced by the absorbed laser energy at the keyhole wall, is a key determining factor for the macroscopic flow of the molten metal in the weld pool during high-power laser beam welding. Consequently, a realistic implementation of the effect of laser radiation on the weld metal is crucial to obtain reliable and accurate simulation results. In this paper, we discuss manyfold different improvements on the laser-material interaction, namely, the ray tracing method, in the numerical simulation of the laser beam welding process. The first improvement relates to locating the exact reflection points in the ray tracing method using a so-called cosine condition in the determination algorithm for the intersection of reflected rays and the keyhole surface. A second correction refers to the numerical treatment of the Gaussian distribution of the laser beam, whose beam width is defined by a decay of the laser intensity by a factor of 1/e2, thus ignoring around 14% of the total laser beam energy. In the third step, the changes in the laser radiation distribution in the vertical direction were adapted by using different approximations for the converging and the diverging regions of the laser beam, thus mimicking the beam caustic. Finally, a virtual mesh refinement was adopted in the ray tracing routine. The obtained numerical results were validated with experimental measurements.
AISI 2205 duplex stainless steel is used in a variety of industries, including the chemical and petrochemical industries. This is due to its high tensile strength combined with good ductility and corrosion resistance. However, in laser beam welding, these properties are negatively afected by the high cooling rates typical of the welding process. The resulting higher ferrrite content in the weld metal than in the base material leads to a reduction in the ductility and corrosion resistance of the welded joint. To overcome this problem, in this study, thick plates were coated by direct energy deposition (DED) prior to laser beam welding, whereas a duplex powder mixture containing a higher nickel concentration was used as a coating material. To improve the weld quality for the proposed two-step process, a method of additional material deposition instead of conventional tack weld was investigated. The resulting welded joints showed a well-balanced austenite to ferrite ratio and their properties and microstructure were verifed by metallographic analysis, electron backscatter difraction and Charpy impact testing. Using the standard ASTM G48 test method, it was found that the corrosion resistance of the welds was improved by a factor of four in average compared to the conventionally welded joints. The resulting properties, such as good ductility and corrosion resistance, of the welds with pre-coated edges showed good agreement with those of the base metal and confrmed the proposed two-step process as a promising alternative to the conventional approaches for welding thick duplex stainless steel plates.
In recent years, in addition to the commonly known wire-based processes of Directed Energy Deposition using lasers, a process variant using the electron beam has also developed to industrial market maturity. The process variant offers particular potential for processing highly conductive, reflective or oxidation-prone materials. However, for industrial usage, there is a lack of comprehensive data on performance, limitations and possible applications. The present study bridges the gap using the example of the high-strength aluminum bronze CuAl8Ni6. Multi-stage test welds are used to determine the limitations of the process and to draw conclusions about the suitability of the parameters for additive manufacturing. For this purpose, optimal ranges for energy input, possible welding speeds and the scalability of the process were investigated. Finally, additive test specimens in the form of cylinders and walls are produced, and the hardness profile, microstructure and mechanical properties are investigated. It is found that the material CuAl8Ni6 can be well processed using wire electron beam additive manufacturing. The microstructure is similar to a cast structure, the hardness profile over the height of the specimens is constant, and the tensile strength
and elongation at fracture values achieved the specification of the raw material.
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.
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.
Friction stir welding (FSW) has the capacity to join the Al/Ti dissimilar structures with superior mechanical properties. The microstructures and mechanical characteristics of Al/Ti dissimilar FSW joints are determined by the heat and mass transfer during the welding process. However, a quantitative study of the Al/Ti dissimilar FSW process is lacking. Therefore, using the computational fluid dynamics (CFD) and volume of fluid (VOF) approach, a multi-phase model was constructed for quantitatively analyzing the heat and mass transfer behaviour in dissimilar FSW of TC4 titanium alloy and AA2024-T4 aluminium alloy. The mixed material was treated as a functionally graded material (FGM) to compute the thermophysical characteristics at the weld nugget zone (WNZ). Due to the vast disparity in the thermophysical characteristics of aluminum and titanium alloy, the temperature field in Al/Ti dissimilar FSW was severely asymmetric. The temperature of titanium alloy on the advancing side (AS) was higher than that of aluminium alloy on the retreating side (RS) at the same distance from the tool centre line near the tool shoulder, but it was lower than that of aluminium alloy on the RS without the influence of the shoulder. Due to the high flow stress of titanium alloy, plastic material flow mostly occurred on the RS of aluminium alloy in the Al/Ti dissimilar FSW, with its percentage exceeding 80%. This model was validated by experiment results.
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.
Understanding the void defect formation mechanism and simultaneous predicting the tool service life in friction stir welding are critical for optimizing the welding parameters. However, the void defect formation mechanism in friction stir welding is not yet elucidated. In this study, a novel integrated thermal-fluid-structure coupling model of the friction stir welding process was proposed for simultaneous prediction of the weld formation and tool service life. A new non-uniform distribution model of the tool-workpiece contact pressure was proposed to describe the interaction between the tool and the workpiece. The void defect formation mechanism was quantitatively studied using the proposed integrated thermal-fluid-structure coupling model. The results show that the plastic material flows in the horizontal direction and can completely fill the cavity behind the tool for the welding condition of forming a sound weld. While the tool-workpiece contact interfacial frictional shear stress in the rear of the tool is decreased significantly which leads to a severe decrease in the plastic material flow velocity. Therefore, after bypassing the tool from the retreating side, the plastic material at the bottom of the weld stagnates, and void defect forms in the middle and lower part of the weld at the advancing side. The difference between the maximum and the minimum tool-workpiece contact pressure could serve as a numerical criterion to predict void defects. A sound joint is formed when the difference is lower than the critical value of 15 MPa, while a void defect is formed in the weld if it is higher than this critical value. The maximum equivalent stress acting on the tool is located at the pin root with severe stress concentration at a high welding speed. The front of the tool is subjected to tensile stress while its rear is subjected to compressive stress, therefore the tool is apt to fracture at its root under an inappropriate welding condition. The average normal stress of the tool varies periodically with its period consistent with the rotation period of the tool. The service life of the tool is decreased with the increase in welding speed and the decrease in rotation speed. The model is validated by experimental results.
The high amount of resource consumption of fusion welding processes offers the potential to reduce their environmental impact. While the driving forces are known froma qualitative perspective, the quantitative assessment of the crucial parameters is not a trivial task. Therefore, herein, a welding-specific methodology to utilize life cycle assessment as a tool for evaluating the environmental impact of fusion welding processes is presented. In this context, two welding processes, resistance spot welding and laser beam welding, are analyzed for two different use cases.
These comprise the welding of shear test specimens and a cap profile made of electrogalvanized sheets of DC 05þ ZE (1.0312) as representative of an automotive application. For both welding processes, the main influences on the resulting environmental impact categories are evaluated and compared. The requirements for ecological efficient welding processes are discussed and implemented.
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.
Directed energy deposition (DED) has been in industrial use as a coating process for many years. Modern applications include the repair of existing components and additive manufacturing. The main advantages of DED are high deposition rates and low energy input. However, the process is influenced by a variety of parameters affecting the component quality. Artificial neural networks (ANNs) offer the possibility of mapping complex processes such as DED. They can serve as a tool for predicting optimal process parameters and quality characteristics. Previous research only refers to weld beads: a transferability to additively manufactured three-dimensional components has not been investigated. In the context of this work, an ANN is generated based on 86 weld beads. Quality categories (poor, medium, and good) are chosen as target variables to combine several quality features. The applicability of this categorization compared to conventional characteristics is discussed in detail. The ANN predicts the quality category of weld beads with an average accuracy of 81.5%. Two randomly generated parameter sets predicted as “good” by the network are then used to build tracks, coatings,walls, and cubes. It is shown that ANN trained with weld beads are suitable for complex parameter predictions in a limited way.