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Laser-based direct energy deposition (DED-LB/M) has been a promising option for the surface repair of structural aluminum alloys due to the advantages it offers, including a small heat-affected zone, high forming accuracy, and adjustable deposition materials. However, the unequal powder particle size during powder-based DED-LB/M can cause unstable flow and an uneven material flow rate per unit of time, resulting in defects such as pores, uneven deposition layers, and cracks. This paper presents a multiscale, multiphysics numerical model to investigate the underlying mechanism during the powder-based DED-LB/M surface repair process. First, the worn surfaces of aluminum alloy components with different flaw shapes and sizes were characterized and modeled. The fluid flow of the molten pool during material deposition on the worn surfaces was then investigated using a model that coupled the mesoscale discrete element method (DEM) and the finite volume method (FVM). The effect of flaw size and powder supply quantity on the evolution of the molten pool temperature, morphology, and dynamics was evaluated. The rapid heat transfer and variation in thermal stress during the multilayer DED-LB/M process were further illustrated using a macroscale thermomechanical model. The maximum stress was observed and compared with the yield stress of the adopted material, and no relative sliding was observed between deposited layers and substrate components.

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To quantitatively evaluate the effect of the process parameters and the material properties on the temperature in laser powder bed fusion (LPBF), this paper proposed a sensitivity analysis of the temperature based on the validated prediction model. First, three different heat source modes-point heat source, Gaussian surface heat source, and Gaussian body heat source-were introduced. Then, a case study of Ti6Al4V is conducted to determine the suitable range of heat source density for the three different heat source models. Based on this, the effects of laser processing parameters and material thermophysical parameters on the temperature field and molten pool size are quantitatively discussed based on the Gaussian surface heat source. The results indicate that the Gaussian surface heat source and the Gaussian body heat source offer higher prediction accuracy for molten pool width compared to the point heat source under similar processing parameters. When the laser energy density is between 40 and 70 J/mm3, the prediction accuracy of the Gaussian surface heat source and the body heat source is similar, and the average prediction errors are 4.427% and 2.613%, respectively. When the laser energy density is between 70 and 90 J/mm3, the prediction accuracy of the Gaussian body heat source is superior to that of the Gaussian surface heat source. Among the influencing factors, laser power exerts the greatest influence on the temperature field and molten pool size, followed by scanning speed. In particular, laser power and scan speed contribute 38.9% and 23.5% to the width of the molten pool, 39.1% and 19.6% to the depth of the molten pool, and 38.9% and 21.5% to the maximum temperature, respectively.

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Selective laser melting (SLM) technology is a promising additive manufacturing technology. However, due to the numerous influencing factors in this complex process, a reliable real-time method is needed to monitor the forming process of SLM. The molten pool is the smallest forming unit in the SLM process, the consistency of which can effectively reflect the quality of the printing process. By using a coaxial optical path structure and a compound amplifier circuit, high-speed acquisition of molten pool radiation can be realized. Next, single factor analysis and orthogonal experimentation were used to investigate the influence levels of key process parameters on the radiation of molten pool. In addition, numerical simulation was carried out with the same parameter setting schemes, the results of which are consistent with those in radiation detection experiments. It is shown that the laser power has the greatest effect on the radiation of the molten pool, while the scanning speed and the hatch spacing have little effect on the radiation. Finally, the positioning experiment involving the small hole structure was carried out, and the experimental results showed that the device could accurately locate the position coordinates of the given hole structure.

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In the selective laser melting (SLM) process, adjusting process parameters contributes to achieving the desired molten pool morphology, thereby enhancing the mechanical properties and dimensional accuracy of manufactured components. The parameter window characterizing the relationship between molten pool morphology and process parameters serves as an effective tool to improve SLM's forming quality. This work established a mesoscale model of the SLM process for a GH3625 alloy based on the discrete element method (DEM) and computational fluid dynamics (CFD) to simulate the forming process of a single molten track. Subsequently, the formation mechanism and evolution process of the molten pool were revealed. The effects of laser power and scanning speed on the molten pool size and molten track morphology were analyzed. Finally, a parameter window was established from the simulation results. The results indicated that reducing the scanning speed and increasing the laser power would lead to an increase in molten pool depth and width, resulting in the formation of an uneven width in the molten track. Moreover, accelerating the scanning speed and decreasing the laser power cause a reduction in molten pool depth and width, causing narrow and discontinuous molten tracks. The accuracy of the simulation was validated by comparing experimental and simulated molten pool sizes.

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Laser polishing is an emerging efficient technique to remove surface asperity without polluting the environment. However, the insufficient understanding of the mechanism of laser polishing has limited its practical application in industry. In this study, a dual-beam laser polishing experiment was carried out to reduce the roughness of a primary Ti6Al4V sample, and the polishing mechanism was well studied using simulation analysis. The results showed that the surface roughness of the sample was efficiently reduced from an initial 10.96 µm to 1.421 µm using dual-beam laser processing. The simulation analysis regarding the evolution of material surface morphology and the flow behavior of the molten pool during laser the polishing process revealed that the capillary force attributed to surface tension was the main driving force for flattening the large curvature surface of the molten pool at the initial stage, whereas the thermocapillary force influenced from temperature gradient played the key role of eliminating the secondary roughness at the edge of the molten pool during the continuous wave laser polishing process. However, the effect of thermocapillary force can be ignored during the second processing stage in dual-beam laser polishing. The simulation result is well in agreement with the experimental result, indicating the accuracy of the mechanism for the dual-beam laser polishing process. In summary, this work reveals the effect of capillary force and thermocapillary force on molten pool flows during the dual-beam laser polishing processes. Moreover, it is also proved that the dual-beam laser polishing process can further reduce the surface roughness of a sample and obtain a smoother surface.

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The finite element (FE) method is used to characterize the thermal gradient, solidification rate, and molten pool sizes of Ti-6Al-4V plates in the process of selective laser melting (SLM). The results are verified by using the computational fluid dynamics (CFD) simulation. The proposed FE model contains a series of toolpath information that is directly converted from a G-code file, including hatch spacing, laser power, layer thickness, dwell time, and scanning speed generated by using Slic3r software from a CAD file. A proposed multi-layer, multi-track FE model is used to investigate the influence of the laser power, scanning speed, and scanning path on the microstructure in the Ti-6Al-4V plate built via SLM. The processing window is also determined based on the proposed FE model. The FE results indicate that, with a decrease in the laser power and an increase in the scanning speed, the morphology of the crystal grains, showing fully columnar crystals, gradually deviates from the fully equiaxed region. The formed grains are dependent on the laser power, scanning speed, and deposition position, but they are not sensitive to the scanning path, and with the deposition from the bottom layer to the top layer, the size of the formed grains is gradually increasing, which shows a good agreement with the experimental results.

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To study the effect of ultrasonic intensity on the microstructure and mechanical properties during the direct energy deposition-Arc (DED-Arc) of ER70S-6 steel alloy, an ultrasound assisted DED-Arc system was developed by coupling ultrasonic energy with the electric arc deposition process. The propagation and vibration distribution of ultrasound in the substrate were analyzed by numerical simulation method. Deposition layers were fabricated using different ultrasonic amplitudes, and the microstructure, microhardness and tensile properties of the fabricated parts were systematically investigated. The results show that as the ultrasonic intensity increased, the grain refinement area expanded from the center of the molten pool to the surrounding area, and the grain morphology transforms from coarse columnar grains to fine equiaxed grains. When the ultrasonic amplitude was 15 µm, the grain refinement area of the cross-section was 94.6%, the average grain size was significantly increased to about grade 6. The microhardness increased by 10.6%. Thousands of ultrasonic cavitation events not only enhance the supercooling and wettability of the melt pool to promote nucleation, but also break the columnar grains into small grains by intense shock waves, which significantly improve the microstructure homogeneity and mechanical properties. The research provides an alternative approach to overcoming the long-standing problem of coarse columnar grains in the field of DED-Arc.

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A transient numerical simulation method is used to investigate the temperature field, velocity field, and solidified field of large-size Waspaloy superalloy during the electroslag remelting (ESR) process. The effects of melting rate, filling rate, and thickness of the slag layer on the molten pool shape and dendrite arm spacing evolution have been discussed. The temperature in the slag pool is high and relatively uniformly distributed, the temperature range is 1690-1830 K. The highest temperature of the melt pool appears in the center of the slag-metal interface, 1686 K. There are two pairs of circulating vortices in the slag pool, the side vortices are caused by the density difference caused by the buoyancy of the slag, the center vortices are the result of the combined action of electromagnetic force and the momentum of the falling metal droplets. The molten pool depth and dendrite arm spacing increase with the increase of melting rate, but the slag layer thickness and electrode filling rate have little effect on the molten pool morphology and dendrite arm spacing if the droplet effect is not taken into account. Considering the morphology and depth of the molten pool as well as the size and distribution uniformity of the dendrite arm spacing, it is appropriate to maintain the melting rate at 5.8 kg/min for the industrial scale ESR process with the ingot diameter of 580 mm.

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To improve the surface roughness of SKD61 die steel and reduce the secondary overflow of the molten pool, a steady magnetic field-assisted laser polishing method is proposed to study the effect of steady magnetic field on the surface morphology and melt pool flow behavior of SKD61 die steel. Firstly, a low-energy pulsed laser is used for the removal of impurities from the material surface; then, the CW laser, assisted by steady magnetic field, is used to polish the rough surface of SKD61 die steel to reduce the material surface roughness. The results show that the steady magnetic field-assisted laser polishing can reduce the surface roughness of SKD61 die steel from 6.1 µm to 0.607 µm, which is a 90.05% reduction compared with the initial surface roughness. Furthermore, a multi-physical-field numerical transient model involving heat transfer, laminar flow and electromagnetic field is established to simulate the flow state of the molten pool on the surface of the SKD61 die steel. This revealed that the steady magnetic field is able to inhibit the secondary overflow of the molten pool to improve the surface roughness of SKD61 slightly by reducing the velocity of the molten pool. Compared with the molten pool depth obtained experimentally, the molten pool depth simulation was 65 µm, representing an error 15.0%, thus effectively demonstrating the accuracy of the simulation model.

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Selective laser melting is a typical powder-bed additive manufacturing technology, for which it is difficult and expensive to observe and measure the molten pool due to its short lifetime and tiny size. This paper introduced a two-stage mesoscopic layer-by-layer simulation framework for the numerical study of the SLM process, where the powder laying and laser scanning are included and conducted alternatively. For the simulation of powder laying, the dynamic behaviors of the particles as well as the particle-particle and particle-scraper interactions are included. For the simulation of laser scanning, a coupled multi-phase and multi-physics system was considered, where the effects of surface tension, Marangoni effect, and vapor recoil are considered, and the behaviors of heat transfer, fluid flow, and melting/solidification are simulated. This simulation framework was then used to simulate the Ti-6Al-4V SLM process. The evolutions of the molten pool and track were presented, and the characteristics of the molten pool, keyhole, and track were analyzed and discussed, specifically, the effects of the laser power and scanning speed on the three-dimensional morphology and size of the molten pool were numerically studied, and their dependencies were discussed and found.

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Ultrashort pulse laser shows good potential for heat control improvement in metal additive manufacturing. The challenge of applying ultrashort pulse laser as the heat source is to form a fully melted and dense microstructure. In this study, a picosecond pulse laser is introduced for fabricating single layer Ti6Al4V samples. The results, by examining through X-ray computed tomography (X-CT), scanning electron microscopy (SEM), show that highly dense Ti6Al4V samples were fabricated with optimized process parameters. The analysis of the cross section presents a three-zones structure from top to bottom in the sequence of the fully melted zone, the partially melted zone, and the heat-affected zone. A semi-quantitative study is performed to estimate the thermal efficiency of melted pool formation. The mechanical properties of the samples are tested using nano-indentation, showing an elastic modulus of 89.74 ± 0.74 GPa. The evidence of dense melted pool with good mechanical properties indicates that the picosecond laser can be integrated as the heat source with the current metal additive manufacturing to fabricate parts with accuracy control for the smaller size of thermal filed.

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A transient three-dimensional (3D) numerical model was established to illustrate the heat transfer, fluid flow and particle migration behaviors in the molten pool during TIG-assisted droplet deposition manufacturing (DDM) of SiC particle-reinforced aluminum matrix composites (AMCs). The effect of temperature-dependent physical properties and the interaction between the SiC reinforcement and the liquid metal matrix were considered. A double-ellipsoidal volumetric heat source model was adopted to simulate the energy interactions between the pulse square-wave variable polarity TIG welding arc and the moving substrate. Free surface fluctuations of molten pool due to arc force and sequential droplet impact are calculated with volume of fluid (VOF) method in a fixed Eulerian structured mesh. The numerical model, capable of capturing the impact, simultaneous spread, and phase change of the droplets as well as the motion trajectory and terminate distribution state of the reinforcement particles, is key tool to understand the formation mechanism of the TIG-assisted DDM of SiC particle-reinforced AMCs. The numerical model was validated by the metallographic observations, and the calculated particle distribution and solidification morphology of deposited layer agree well with the experimental measurements.

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OBJECTIVES: The application of selective laser melting (SLM) to dentistry has been rapidly expanding; however, SLM-processed parts possess orientation-dependent properties (i.e., anisotropy) that can affect the long-term reliability of the dental prostheses. This study aimed to evaluate the anisotropic corrosion response of SLM-processed Co-Cr-Mo alloys under various heat treatments. METHODS: Samples fabricated via SLM along the horizontal plane (x-y plane) and vertical plane (x-z plane), with respect to the build direction, were subjected to various heat treatments. The resulting microstructures of the samples were characterized, and their corrosion properties were evaluated using anodic polarization and immersion tests. RESULTS: All samples showed similar transpassive behavior of the polarization curves. However, the immersion tests showed that the as-built x-z plane samples released significantly more metal ions than those fabricated on the x-y plane because of the larger area of preferentially corroded molten pool boundaries (MPBs) in the x-z plane samples. Our results further demonstrated that the heat treatments eliminated the MPBs, resulting in isotropic corrosion properties. However, excessive heat treatment at high temperatures induces the formation of coarse precipitates, resulting in a less-protective passive film. SIGNIFICANCE: The post-build heat treatments at temperatures that eliminate the MPBs are effective in reducing anisotropic corrosion behavior, and the lowest possible temperature is suitable for reducing the amount of released metal ions. These findings are expected to facilitate the application of SLM in dentistry to allow fast and precise production of prosthetic devices.

Asunto(s)

Aleaciones , Calor , Anisotropía , Aleaciones de Cromo , Corrosión , Aleaciones Dentales , Rayos Láser , Reproducibilidad de los Resultados , Propiedades de Superficie

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The process parameters of selective laser melting (SLM) significantly influence molten pool formation. A comprehensive understanding and analysis, from a macroscopic viewpoint, of the mechanisms underlying these technological parameters and how they affect the evolution of molten pools are presently lacking. In this study, we established a dynamic finite element simulation method for the process of molten pool formation by SLM using a dynamic moving heat source. The molten pool was generated, and the dynamic growth process of the molten pool belt and the evolution process of the thermal field of the SLM molten pool were simulated. Then, a deposition experiment that implemented a new measurement method for online monitoring involving laser supplementary light was conducted using the same process parameters as the simulation, in which high-speed images of the molten pool were acquired, including images of the pool surface and cross-section images of the deposited samples. The obtained experimental results show a good agreement with the simulation results, demonstrating the effectiveness of the proposed algorithm.

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In this study, the phase transition of secondary phase particles in a composite coating is used to estimate the temperature field of the molten pool on a Ti6Al4V alloy in the micro-arc oxidation (MAO) process. The behavior of the sparks and the molten pool during the MAO process was observed in real-time by a long-distance microscope. The microstructures and compositions of the composite coatings were studied by scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), and X-ray diffraction (XRD). The results revealed that, for the temperature field distribution range of the molten pool in the active period, the lower limit is 2123 K and the upper limit is not lower than 3683 K. The reason for the multiphase coexistence is that the high-temperature phase is retained by the rapid cooling effect of the electrolyte, and the low-temperature phase is formed due to secondary phase transformation during the long active time of the molten pool temperature field. The strengthening mechanism of the composite coating prepared by adding the secondary phase particles is elemental doping rather than particle enhancement. The secondary phase particles are able to enter the composite coating by adhering to the surface during the cooling process. The secondary phase particles will then be wrapped into the coating in the next active period.

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The dynamic behavior of the keyhole and molten pool is associated with the quality of weld seam. In this study, an on-line visual monitoring system is devised to photograph the keyhole and molten pool during external magnetic field assisted laser welding on the AISI 2205 duplex stainless steel plates. Seven features are defined to describe the morphology of the keyhole and molten pool. Then, the principal component analysis (PCA) algorithm is applied to reduce the dimensions of these features to obtain different number of principal components (PCs). Three different machine learning algorithms, i.e. the back propagation neural network (BPNN), the radial based function neural network (RBFNN) and the support vector regression (SVR), are utilized to fit the relationship between the chosen PCs and the weld width. Finally, the global and local prediction accuracy of these three machine learning algorithms are compared under different number of PCs. Results illustrated that data dimensionality reduction is helpful to improve the modeling efficiency. Machine learning algorithms can be exploited to predict the weld quality during laser welding with high accuracy. Among them, the BPNN model performs best and SVR model performs better than RBFNN model in this research. This work aims to model the relation between the features in weld zone and the weld quality with different machine learning algorithms, and provides a guideline of model selection for laser welding on-line monitoring and a necessary foundation for realizing intelligent welding with advanced algorithm.

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Nickel-based superalloys are one of the most industrially important families of metallic alloys at present. Selective Laser Melting (SLM), as one of the additive manufacturing technologies for directly forming complex metal parts, has been applied in the production of Inconel 718 components. Based on the more reasonable and comprehensive equivalent processing models (vaporization heat loss, equivalent physical parameters) for the nickel-based superalloy SLM process, an SLM molten pool dynamic behavior prediction model on the workpiece scale was established. Related equivalent processing models were customized by secondary development with the software Fluent. In order to verify the feasibility of the SLM molten pool dynamics model, the SLM single-pass employed to form the Inconel 718 alloy process was calculated. The simulated and experimental solidified track dimensions were in good agreement. Then, the influences of different process parameters (laser power, scanning speed) on the SLM formation of the Inconel 718 alloy were calculated and analyzed. The simulation and experimental solidified track widths were well-matched, and the result showed that, as a rule, the solidified track width increased linearly with the laser power and decreased linearly with the scanning speed. This paper will help lay the foundation for a subsequent numerical simulation study of the thermal-melt-stress evolution process of an SLM workpiece.

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Temperature distribution gradient in metal powder bed additive manufacturing (MPBAM) directly controls the mechanical properties and dimensional accuracy of the build part. Experimental approach and numerical modeling approach for temperature in MPBAM are limited by the restricted accessibility and high computational cost, respectively. Analytical models were reported with high computational efficiency, but the developed models employed a moving coordinate and semi-infinite medium assumption, which neglected the part dimensions, and thus reduced their usefulness in real applications. This paper investigates the in-process temperature in MPBAM through analytical modeling using a stationary coordinate with an origin at the part boundary (absolute coordinate). Analytical solutions are developed for temperature prediction of single-track scan and multi-track scans considering scanning strategy. Inconel 625 is chosen to test the proposed model. Laser power absorption is inversely identified with the prediction of molten pool dimensions. Latent heat is considered using the heat integration method. The molten pool evolution is investigated with respect to scanning time. The stabilized temperatures in the single-track scan and bidirectional scans are predicted under various process conditions. Close agreements are observed upon validation to the experimental values in the literature. Furthermore, a positive relationship between molten pool dimensions and powder packing porosity was observed through sensitivity analysis. With benefits of the absolute coordinate, and high computational efficiency, the presented model can predict the temperature for a dimensional part during MPBAM, which can be used to further investigate residual stress and distortion in real applications.

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At present, realizing high-quality automatic welding through online monitoring is a research focus in engineering applications. In this paper, a CNN⁻LSTM algorithm is proposed, which combines the advantages of convolutional neural networks (CNNs) and long short-term memory networks (LSTMs). The CNN⁻LSTM algorithm establishes a shallow CNN to extract the primary features of the molten pool image. Then the feature tensor extracted by the CNN is transformed into the feature matrix. Finally, the rows of the feature matrix are fed into the LSTM network for feature fusion. This process realizes the implicit mapping from molten pool images to welding defects. The test results on the self-made molten pool image dataset show that CNN contributes to the overall feasibility of the CNN⁻LSTM algorithm and LSTM network is the most superior in the feature hybrid stage. The algorithm converges at 300 epochs and the accuracy of defects detection in CO2 welding molten pool is 94%. The processing time of a single image is 0.067 ms, which fully meets the real-time monitoring requirement based on molten pool image. The experimental results on the MNIST and FashionMNIST datasets show that the algorithm is universal and can be used for similar image recognition and classification tasks.

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Due to the rapid melting and solidification mechanisms involved in selective laser melting (SLM), CoCrMo alloys fabricated by SLM differ from the cast form of the same alloy. In this study, the relationship between process parameters and the morphology and macromechanical properties of cobalt-chromium alloy micro-melting pools is discussed. By measuring the width and depth of the molten pool, a theoretical model of the molten pool is established, and the relationship between the laser power, the scanning speed, the scanning line spacing, and the morphology of the molten pool is determined. At the same time, this study discusses the relationship between laser energy and molding rate. Based on the above research, the optimal process for the laser melting of cobalt-chromium alloy in the selected area is obtained. These results will contribute to the development of biomedical CoCr alloys manufactured by SLM.