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Laser metal deposition (LMD) is an established technology for two-dimensional surface coatings. It offers high deposition rates, high material flexibility, and the possibility to deposit material on existing components. Due to these features, LMD has been increasingly applied for additive manufacturing of 3D structures in recent years. Compared to previous coating applications, additive manufacturing of 3D structures leads to new challenges regarding LMD process knowledge. In this paper, the process steps for LMD as additive manufacturing technology are described. The experiments are conducted using titanium alloy Ti-6Al-4Vand Inconel 718. Only the LMD nozzle is used to create a shielding gas atmosphere. This ensures the high geometric flexibility needed for additive manufacturing, although issues with the restricted size and quality of the shielding gas atmosphere arise. In the first step, the influence of process parameters on the geometric dimensions of single weld beads is analyzed based on design of experiments. In the second step, a 3D build-up strategy for cylindrical specimen with high dimensional accuracy is described. Process parameters, travel paths, and cooling periods between layers are adjusted. Tensile tests show that mechanical properties in the as-deposited condition are close to wrought material. As practical example, the fir-tree root profile of a turbine blade is manufactured. The feasibility of LMD as additive technology is evaluated based on this component.
The prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing
workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers.
Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. Themodel is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) μm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample
labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity.
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.
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.
Sample functions, i.e., stochastic process realizations, are used to define cumulative damage phenomena which end into an observable terminal state or failure. The complexity inherent to such phenomena justifies the use of phenomenological models associated with the evolution of a physical magnitude feasible to be monitored during the test. Sample functions representing the damage evolution may be identified, once normalized to the interval [0,1], with cumulative distribution functions (cdfs), generally, of the generalized extreme value (GEV) family. Though usually only a fraction of the whole damage evolution, according to the specific problem handled, is available from the test record, the phenomenological models proposed allow the whole damage process to be recovered. In this way, down- and upwards extrapolations of the whole damage process beyond the scope of the experimental program are provided as a fundamental tool for failure prediction in the practical design. The proposed methodology is detailed and its utility and generality confirmed by its successive application to representative well-known problems in fatigue and fracture characterization. The excellent fittings, the physical interpretation of the model parameters and the good expectations to achieve a complete probabilistic analysis of these phenomena justify the interest of the proposed phenomenological approach with possible applications to other cumulative damage processes.
A simplified model for numerical simulation of laser metal deposition process with beam oscillation
(2018)
A model of laser metal deposition with beam oscillation has been developed. The proposed model consists of two coupled sub-models calculating the heat transfer in the deposited part and the free surface of the molten pool, respectively. The heat transfer simulation of the deposited part solves a three-dimensional quasi-stationary heat conduction problem. The free surface of the molten pool are determined by solving the Laplace-Young equation. The developed model enables the layer-by-layer prediction of the shape of the deposited part and the resulting temperature field. It is shown that for an oscillation amplitude equal to the beam radius the peak value of the heat flux decreases by about 53% and 73% in the case of lateral oscillation and circular oscillation, respectively. Lateral oscillating laser beam results in a higher penetration depth due to the higher thermal efficiency. The amplitude of the laser beam oscillation effects the shape of the deposited wall and the deposition rate. A good correlation between the numerically calculated and experimentally observed results is obtained.
In this paper, the highly transient keyhole dynamics, e.g., laser absorption, keyhole geometry, and fluctuation, etc., under a magnetic field are investigated using an experimental approach and multi-physical modeling. The model provides accurate predictions to the variation of penetration depth and weld pool profiles caused by the MHD effect, which is validated by the measurements of optical micrographs and in-situ metal/glass observation. The micro-X-ray computed tomography shows a remarkable reduction of keyhole-induced porosity with the magnetic field. The correlation between the porosity mitigation and the weld pool dynamics influenced by the magnetic field is built comprehensively. It is found that the magnetic field gives a direct impact on the laser energy absorption at the keyhole front wall by changing the protrusion movement. The porosity mitigation comes from multiple physical aspects, including keyhole stabilization, widening of the bubble floating channel, and the electromagnetic expulsive force. Their contributions vary according to the bubble size. The findings provide a deeper insight into the relationship between electromagnetic parameters, keyhole dynamics, and suppression of keyhole-relevant defects.
Carbidic Austempered Ductile Iron (CADI) microstructures containing eutectic carbides can be produced by the addition of carbide stabilizing elements, such as chromium. Carbides formed from the addition of Cr are eutectic of M3C type. The presence of such hard phases can enhance the abrasion wear resistance of ductile iron. A new CADI can be produced by the addition of Nb. Niobium carbide particles are formed in the beginning of solidification and remain stable once they are insoluble in solid iron matrix. The dry sand abrasive wear resistance of ductile irons alloyed with 1.0, 1.8, and 2.4 wt% Nb were tested in both “as-cast” and “heat treated” conditions using standard ASTM G65. Results were compared to abrasive wear data obtained on ductile iron alloyed with 1 wt% Cr, CADI (1 wt% Cr), and the basic composition of iron without carbide stabilizing elements. In the “ascast” condition, the addition of Nb did not lead to a reduction in wear, while CADI with Nb is a promising substitute for CADI with Cr addition, because both materials showed very similar values of abrasion resistance.
Micro-ploughing and micro-cutting mechanisms were observed on the worn surfaces of ductile irons. Abrasive wear resistance of these alloys was correlated with the volume fraction of carbides.
Alloy 36 (1.3912) is an alloy with 36% nickel and 64% iron and is generally classified as a difficult-to-cut material. Increasingly complex structures and the optimization of resource efficiency are making additive manufacturing (AM) more and more attractive for the manufacture or repair of components. Subsequent machining of AM components is unavoidable for its final contour. By using modern, hybrid machining processes, e.g., ultrasonic-assisted milling (US), it is possible to improve the cutting situation regarding the resulting surface integrity as well as the cutting force. Part I deals with the influence of the alloying elements Ti, Zr, and Hf on the microstructure and the hardness of the initial alloy 36. Part II focusses on the effect of the alloy modifications and the ultrasonic assistance on machinability as well as on the surface integrity after finish-milling. The results show a highly significant influence of the ultrasonic assistance. The cutting force during the US is reduced by over 50% and the roughness of approx. 50% compared to conventional milling (CM) for all materials investigated. Moreover, the US causes a defect-free surface and induces near-surface compressive residual stresses. CM leads to a near-surface stress state of approx. 0 MPa.