Laser Powder Bed Fusion Parts Research Articles

Interpenetrating microstructure in laser powder-bed fusion parts using selective rescanning

In-situ microstructural control is desirable in additively manufactured metal parts due to limited post-processing options for net-shaped components. Here, we introduce a novel selective rescanning approach to control the local solidification conditions and the microstructure in metal parts produced by laser powder-bed fusion (LPBF). We show that the melt pool dimensions, grain size, and sub-grain cell structure can be selectively varied in three dimensions to engineer the mechanical response of LPBF parts. The lattice-based rescanning strategy enables the formation of an interpenetrating microstructure comprised of fine and coarse grains. The localized heating and cooling-induced thermal stresses increase the hardness and tensile strength of rescanned specimens. The study shows the potential of selective rescanning strategy as a promising avenue for achieving precise control of microstructure and properties in as-printed LPBF parts without subsequent processing.

Multi-objective optimization of parts construction direction by scaling-enumeration method in L-PBF process

PurposePart building orientation (PBO) is an important factor affecting the quality of laser powder bed fusion (L-PBF), which can affect the surface quality and manufacturing cost. The purpose of this paper is to propose a PBO optimization method to optimize the surface roughness and molding time of parts at the same time on the premise of small calculation scale and arbitrary resolution.Design/methodology/approachEfficient and accurate evaluation is an important index of PBO optimization method. In this paper, a PBO optimization method based on scaling enumeration method is proposed, and the surface roughness and molding time of L-PBF parts are modeled as the objective evaluation function of PBO optimization process. To realize multi-objective optimization, an expert system is established, and the fuzzy multiple-attribute group decision-making theory is used to provide weights for each objective evaluation function.FindingsResearch shows that the scaling-enumeration method can optimize the surface roughness and molding time at the same time and get the best PBO. Compared with the traditional method, the surface roughness and molding time are reduced by 1.1% and 0.58%, respectively, and the operation scale of the scaling-enumeration method is reduced by 99% compared with the traditional method. PBO with arbitrary angular resolution can be achieved.Originality/valueThis paper presents a new method to optimize the forming direction of L-PBF parts. This method has small operation scale and accurate results, so it is meaningful for industrial application.

Correlative spatter and vapour depression dynamics during laser powder bed fusion of an Al-Fe-Zr alloy

Spatter during laser powder bed fusion (LPBF) can induce surface defects, impacting the fatigue performance of the fabricated components. Here, we reveal and explain the links between vapour depression shape and spatter dynamics during LPBF of an Al-Fe-Zr aluminium alloy using high-speed synchrotron x-ray imaging. We quantify the number, trajectory angle, velocity, and kinetic energy of the spatter as a function of vapour depression zone/keyhole morphology under industry-relevant processing conditions. The depression zone/keyhole morphology was found to influence the spatter ejection angle in keyhole versus conduction melting modes: (i) the vapour-pressure driven plume in conduction mode with a quasi-semi-circular depression zone leads to backward spatter whereas; and (ii) the keyhole rear wall redirects the gas/vapour flow to cause vertical spatter ejection and rear rim droplet spatter. Increasing the opening of the keyhole or vapour depression zone can reduce entrainment of solid spatter. We discover a spatter-induced cavity mechanism in which small spatter particles are accelerated towards the powder bed after laser-spatter interaction, inducing powder denudation and cavities on the printed surface. By quantifying these laser-spatter interactions, we suggest a printing strategy for minimising defects and improving the surface quality of LPBF parts.

Influence of Pre- and Post-Contouring Strategies to Downskin Sloped Surfaces in Laser Powder-Bed Fusion (L-PBF) Additive Manufacturing.

Among various metal additive manufacturing (AM) technologies, L-PBF is known for fabricating intricate components. However, due to step edges and powder particle attachments, attaining a good surface finish is challenging, especially on downskin surfaces. Contour scanning has potential to improve surface quality because such scanning may dominate the surface formation of sloped features. This study evaluates the effects of pre- and post-contouring strategies on the sloped downskin surfaces fabricated using a commercial L-PBF system with Ti6Al4V powder. L-PBF parts printed at inclination angles 30°, 45° and 60° were investigated. A double-contouring approach with varying processing conditions was employed and surface characteristics were analyzed using data acquired by white light interferometry. The average surface roughness, Sa, surface skewness, Ssk, and percentage area of powder particles attached onto surfaces were statistically evaluated. The lowest Sa obtained for pre- and post-contoured samples is 14.08 µm and 18.88 µm, respectively. For both strategies, the combination of a low laser power and a high scan speed on the interface of downskin surface and underneath powder results in smoother surfaces. However, while comparing both strategies, pre-contouring gives better surface finish for samples built at similar processing conditions, with a difference of nearly 5 µm in Sa.

Effect of heat treatment on microstructure and mechanical characteristics of laser powder bed fusion (LPBF) produced CuCrZr alloy

In this work, the CuCrZr alloy was fabricated by employing the laser powder bed fusion (LPBF) process. For elevating the mechanical characteristics offered by the LPBF parts, heat treatment was performed and three cooling pathways such as water quenching, air cooling and furnace cooling were adapted. The obtained results showed that the water quenching leads to the formation of more craters in its microstructure compared to the air cooled and furnace cooled samples. The nanoindentation analysis revealed that the furnace cooled sample had higher hardness (1.56 GPa) which is attributed to the precipitation of Cu-Zr intermetallic precipitates. Moreover, this sample tends to have a low wear rate and higher tensile characteristics due to the formation of intermetallic precipitates.

Effects of process parameters and geometry on dimensional accuracy and surface quality of thin strut heart valve frames manufactured by laser powder bed fusion

Laser powder bed fusion (LPBF) is one of the most popular metal additive manufacturing technologies, which has found its applications in high-value sectors such as aerospace and biomedical devices. Some recent studies on the LPBF of stents have demonstrated its feasibility in the fabrication in thin strut structures including heart valve frames, as used in transcatheter aortic valve implantation (TAVI) for the treatment of severe aortic stenosis. The state of the art method of laser cutting TAVI frame limits the scope for novel concepts which are made possible by additive manufacturing. However, the surface quality and dimensional accuracy of LPBF parts are lower than that produced by laser cutting. To start the development of new TAVI concepts, the feasibility of manufacturing thin frames by LPBF has been investigated based on the SAPIEN 3 frame by Edwards Lifesciences. In this study, simplified frames with strut size from 0.3 to 0.5 mm have been successfully manufactured. The effects of strut size, strut angle, laser power and scan speed on the dimensional accuracy and surface quality were systemically studied. In addition, a representative SAPIEN 3 frame was manufactured and assessed with high-resolution X-ray CT scans. Good overall dimensional accuracy and low porosity were obtained for the SAPIEN 3 frame. However, inclined struts were found to have relatively low dimensional accuracy and poor surface quality.

On the role of flat-top beam in pore elimination and fatigue performance of Ti-6Al-4V fabricated by laser powder bed fusion

It's unavoidable to produce defects in the repeated layer-by-layer manufacturing process of laser powder bed fusion (LPBF). This limits the application of LPBF for safety–critical parts. The formation of defects is closely related to the interaction between the laser beam and material in the molten pool. In this paper, beam shaping was used to improve the building quality of LPBF. Process parameter optimization was performed to obtain samples with the fewest defects. Heat treatment was also employed to further improve the mechanical properties. The results showed that the obtained flat-top beam significantly reduced the propensity for keyhole pore formation and enlarged the process windows. In-situ heat treatment induced by high heat input led to the decomposition of martensite and improved the fatigue crack growth (FCG) threshold (∼3.7 MPa m0.5) of the as-built samples. After heat treatment (annealed and solution/aged), the FCG threshold further increased to 5.5/6.3 MPa m0.5, respectively. Reduced defects and high FCG resistance resulted in a fatigue limit above 600 MPa (N = 1e7, R = 0.1), which is comparable to wrought and aged Ti-6Al-4V parts. This study demonstrates the feasibility of improving molten pool stability and reducing defects through beam shaping, providing a new approach to manufacturing high-quality LPBF parts.

Incorporating surface roughness into numerical modeling for predicting fatigue properties of L-PBF AlSi10Mg specimens

Laser-powder bed fusion (L-PBF) is a popular additive manufacturing method for fabricating metal parts with complex geometries. However, one of the primary setbacks lies in the surface quality of the as-built components. Poor surface quality influences the dynamic fatigue properties of L-PBF parts. Experimental investigation of fatigue properties is time-intensive and expensive. Hence, computational modeling can be implemented to critically evaluate the impact of surface roughness on fatigue. In this work, a numerical modeling framework is developed that considers the influence of part-scale surface roughness on fatigue properties. To calibrate and validate the numerical modeling framework, mechanical investigations of miniature AlSi10Mg specimens are conducted in a custom-built tensile-fatigue testing apparatus. First, the tensile properties are evaluated to find out the reliability of the apparatus. Thereafter, the fatigue investigations of two sets of specimens are conducted: five specimens (FS1-FS5) for calibrating the numerical model and three specimens (VFS1-VFS3) for model validation. The numerical modeling framework involves the 3D reconstructed specimen geometries from computed tomography (CT) imaging of the VFS1-VFS3 specimens. The resultant 3D geometries are discretized using Ansys finite element software and analyzed to simulate the fatigue behavior. The numerical results of fatigue life and failure locations of the VFS1-VFS3 specimens are compared with the experimental observations. The comparison shows that the numerical results are within 5 % of the experimental observations. Additionally, the location of maximum strain localization in numerical modeling matches the crack initiation location. In conclusion, the numerical modeling can predict low cycle fatigue life and failure location of L-PBF AM specimens.

Simultaneous Pore Detection and Morphological Features Extraction in Laser Powder Bed Fusion with Image Processing.

Internal pore defects are inevitable during laser powder bed fusion (LPBF), which have a significant impact on the mechanical properties of the parts. Therefore, detecting pores and obtaining their morphology will contribute to the quality of LPBF parts. Currently, supervised models are used for defect image detection, which requires a large amount of LPBF sample data, image labeling, and computing power equipment during the training process, resulting in high detection costs. This study extensively collected LPBF sample data and proposed a method for pore defect classification by obtaining its morphological features while detecting pore defects in optical microscopy (OM) images under various conditions. Compared with other advanced models, the proposed method achieves better detection accuracy on pore defect datasets with limited data. In addition, quickly detecting pore defects in a large number of labeling ground truth images will also contribute to the development of deep learning. In terms of image segmentation, the average accuracy scores of this method in the test images exceed 85%. The research results indicate that the algorithm proposed in this paper is suitable for quickly and accurately identifying pore defects from optical microscopy images.

Process Optimization of SiC-Reinforced Aluminum Matrix Composites Prepared Using Laser Powder Bed Fusion and the Effect of Particle Morphology on Performance.

Process parameters and powder spreading quality are important factors for aluminum matrix composites (AMCs) prepared using laser powder bed fusion (LPBF). In this study, a Box-Behnken Design (BBD) was used to optimize the process parameters, and near-spherical β-SiC was selected to improve the quality of powder spreading. The rationality of parameter optimization was verified by testing the density of samples prepared using different laser power levels. Al4C3 diffraction peaks were found in XRD patterns, which indicated that interface reactions occurred to form good interface bonding between the Al matrix and the SiC particles. The tensile strength and plasticity of LPBF α-SiC/AlSi10Mg were lower than that of LPBF AlSi10Mg, which was mainly due to the poor fluidity of the powder mixtures and powder spreading quality. For LPBF β-SiC/AlSi10Mg, the tensile strength increased and elongation decreased slightly compared to LPBF α-SiC/AlSi10Mg. The data in this study were compared with the data in other studies. In this study, LPBF AlSi10Mg and LPBF β-SiC/AlSi10Mg not only showed the inherent high strength of their LPBF parts, but also had relatively high plasticity. Matching between strength and plasticity was mainly dependent on the scanning strategy. Most studies use uni-directional or bi-directional scanning strategies with a certain rotation angle between layers. A chessboard scanning strategy was used in this study to form a coarse remelted connected skeleton inside the material and significantly improve plasticity. This study lays a theoretical and experimental foundation for the controllable preparation of SiC-reinforced AMCs using LPBF.

In situ three-dimensional reconstruction of laser powder bed fusion parts by light field camera

The assessment of output quality in the laser powder bed fusion process entails the analysis of the three-dimensional morphology of the manufactured parts, which plays a crucial role in quality control to prevent metallurgical defects. This study proposes a novel approach of three-dimensional reconstruction for laser powder bed fusion parts using a light field camera. Initially, a consistency method for high-precision camera calibration was explored to determine the virtual camera pixel size and coefficient of effective focal length of light field camera. Subsequently, the model based light field epipolar-plane image Unet is designed to obtain disparity information without any data augmentation techniques. By leveraging both binocular and light field optical paths, a robust mapping relationship of the disparity, depth, and visually coherent three-dimensional contour was established. Finally, the three-dimensional contours of laser powder bed fusion parts were reconstructed by the established mapping with a single exposure of the light field camera. The proposed method enables three-dimensional contour visualization of laser powder bed fusion parts from multi-view perspectives, which facilitates in situ monitoring of the spattering distance, three-dimensional spatial points and lines of the printed layers and contours of printed parts. With a calibration error of 50 μm and resolution of 180 μm for the light field camera (Lytro illum camera), the maximum relative and absolute errors between reconstructed three-dimensional spatial points were 4.33 % and 260 μm respectively when compared with theoretical dimension, and 0.5 % and 210 μm respectively when compared with manufactured dimension. The maximum root-mean-square error of reconstructed three-dimensional contour surfaces was found to be 1.55 mm. This study represents the first application of a light field camera for in situ three-dimensional reconstruction of laser powder bed fusion parts, which notably can be obtained from only a single round of calibration and exposure, enabling seamless monitoring of their surface morphology and facilitating online quality control. These advancements have vast potential for enhancing high-end additive manufacturing.

Effect of Hirtisation treatment on surface quality and mechanical properties of AlSi10Mg samples produced by laser powder bed fusion

Laser Powder Bed Fusion (L-PBF) provides a larger design freedom than conventional manufacturing techniques. Surface post-processing is widely investigated to improve the roughness of as built L-PBF parts by reducing powder sintered to the surface and the staircase effect, but it becomes even more important to guarantee a smooth surface if support structures are included for tilted overhanging structures. This study focuses on L-PBF AlSi10Mg samples with a building angle of 30° with respect to the baseplate. This building angle inevitably requires support structures. The study investigates if a hybrid surface treatment combining chemical and electrochemical polishing, called Hirtisation®, removes the support structure and to what extent it improves the surface roughness of samples with a 30° building angle. Currently, the results of surface treatments are mostly reported on vertically built samples while down-facing areas of samples with a lower building angle are typically the roughest areas of the samples causing crack initiation in fatigue. Roughness, defect population, residual stresses, microstructure, fatigue, and tensile properties are studied to investigate correlations with the physical effect of Hirtisation. A porous zone is observed in the down-facing area close to the support structures of as built samples. Hirtisation removed successfully the support and the porous area. In the down-facing roughest area, the average values of the average roughness, mean roughness depth and deepest valley depth are reduced by respectively 56,5%, 58,7% and 51,5% by Hirtisation compared to the as built state. The deepest valley measured reduced from 155,5 µm to 74,4 µm. Hirtisation combined with annealing increased the fatigue resistance at a stress amplitude of 120 MPa with a factor 3,1 compared to the as built state and with a factor 2,7 compared to the annealing state. The improved fatigue resistance is linked to halving the deepest valley depth as well as a change in the residual stress at the outer surface from tensile stresses after annealing to a small compressive stress after Hirtisation which counteracts the tensile load in fatigue. Hence, Hirtisation reduces roughness, inverses a tensile residual stress at the outer surface to a small compressive residual stress. In addition, the chemical-electrochemical process allows to access areas which are impossible to post-process with e.g. sandblasting or vibratory polishing. These conclusions make Hirtisation interesting for further investigations for future applications, however the deepest valley depth could be reduced more by increasing the material removal in the process to improve the fatigue life more.

Optimisation of process parameters for improving surface quality in laser powder bed fusion

Surface quality is one of the critical factors that affect the performance of a laser powder bed fusion part. Optimising process parameters in process design is an important way to improve surface quality. So far, a number of optimisation methods have been presented within academia. Each of these methods can work well in its specific context. But they were established on a few special surfaces and may not be capable to produce satisfying results for an arbitrary part. Besides, they do not consider the simultaneous improvement of the quality of multiple critical surfaces of a part. In this paper, an approach for optimising process parameters to improve the surface quality of laser powder bed fusion parts is proposed. Firstly, Taguchi optimisation is performed to generate a small number of alternative combinations of the process parameters to be optimised. Then, actual build and measurement experiments are conducted to obtain the quality indicator values of a certain number of critical surfaces under each alternative combination. After that, a flexible three-way technique for order of preference by similarity to ideal solution is used to determine the optimal combination of process parameters from the generated alternatives. Finally, a case study is presented to demonstrate the proposed approach. The demonstration results show that the proposed approach only needs a small amount of experimental data and takes into account the simultaneous improvement of the quality of multiple critical surfaces of an arbitrary part.

Predicting meltpool depth and primary dendritic arm spacing in laser powder bed fusion additive manufacturing using physics-based machine learning

The long-term goal of this work is to predict and control the microstructure evolution in metal additive manufacturing processes. In pursuit of this goal, we developed and applied an approach which combines physics-based thermal modeling with machine learning to predict two important microstructure-related characteristics, namely, the meltpool depth and primary dendritic arm spacing in Nickel Alloy 718 parts made using the laser powder bed fusion (LPBF) process. Microstructure characteristics are critical determinants of functional physical properties, e.g., yield strength and fatigue life. Currently, the microstructure of LPBF parts is optimized through a cumbersome build-and-characterize empirical approach. Rapid and accurate models for predicting microstructure evolution are therefore valuable to reduce process development time and achieve consistent properties. However, owing to their computational complexity, existing physics-based models for predicting the microstructure evolution are limited to a few layers, and are challenging to scale to practical parts. This paper addresses the aforementioned research gap via a novel physics and data integrated modeling approach. The approach consists of two steps. First, a rapid, part-level computational thermal model was used to predict the temperature distribution and cooling rate in the entire part before it was printed. Second, the foregoing physics-based thermal history quantifiers were used as inputs to a simple machine learning model (support vector machine) trained to predict the meltpool depth and primary dendritic arm spacing based on empirical materials characterization data. As an example of its efficacy, when tested on a separate set of samples from a different build, the approach predicted the primary dendritic arm spacing with root mean squared error ≈ 110 nm. This work thus presents an avenue for future physics-based optimization and control of microstructure evolution in LPBF.

Generating synthetic as-built additive manufacturing surface topography using progressive growing generative adversarial networks

Numerically generating synthetic surface topography that closely resembles the features and characteristics of experimental surface topography measurements reduces the need to perform these intricate and costly measurements. However, existing algorithms to numerically generated surface topography are not well-suited to create the specific characteristics and geometric features of as-built surfaces that result from laser powder bed fusion (LPBF), such as partially melted metal particles, porosity, laser scan lines, and balling. Thus, we present a method to generate synthetic as-built LPBF surface topography maps using a progressively growing generative adversarial network. We qualitatively and quantitatively demonstrate good agreement between synthetic and experimental as-built LPBF surface topography maps using areal and deterministic surface topography parameters, radially averaged power spectral density, and material ratio curves. The ability to accurately generate synthetic as-built LPBF surface topography maps reduces the experimental burden of performing a large number of surface topography measurements. Furthermore, it facilitates combining experimental measurements with synthetic surface topography maps to create large data-sets that facilitate, e.g. relating as-built surface topography to LPBF process parameters, or implementing digital surface twins to monitor complex end-use LPBF parts, amongst other applications.

Processability and Solidification Microstructure of Al-10Si-4.5Mg Alloy Fabricated by Laser Powder Bed Fusion

With the aim of developing a high-strength aluminum alloy for laser powder bed fusion (L-PBF), an Al–10Si–4.5Mg alloy with the a-Al/Si/Mg2Si three-phase microstructure was investigated. The Al–10Si–4.5Mg alloy processed by L-PBF exhibited a fine cellular microstructure including fine granular Mg2Si phases, and therefore exhibited a higher hardness of 187 HV0.1 than those of the conventional Al–Si–Mg alloy. However, cracks were macroscopically propagated between the internal fabrication voids along the melt pool boundaries in the L-PBF processed samples, resulting in a limited relative density below 95.5%. The cracking could be attributed to the relatively coarse Mg2Si particles decorated with the eutectic network. Although the improved strength suggests the advantage of strengthening by the Mg2Si phase, further optimization of the processing conditions will be required to manufacture the intact L-PBF parts.

Design of a Cost-Effective and Statistically Validated Test Specification with Selected Machine Elements to Evaluate the Influence of the Manufacturing Process with a Focus on Additive Manufacturing

Due to their versatile advantages, the use of additively manufactured components is growing. In addition, new additive manufacturing processes are constantly being developed, so that a wide range of printing processes are now available for metal. Despite the same starting material, the microstructure and thus also the final mechanical properties differ greatly compared to conventional processes. In most cases, only direction-dependent characteristic values from the uniaxial tension are used to qualify a printing process before it is used. The literature, on the other hand, demonstrates that the results are not transferable to other loading conditions. In this work, several engineering tests were integrated into a single test specimen so that they can be determined on the same specimen. The test specimen can be used to test tooth root strength, bending strength, notched bar impact energy, and thread strength depending on the mounting direction, thus representing industrial loading cases. In this study, test specimens were fabricated by conventional manufacturing (machining), L-PBF (Laser Powder Bed Fusion), and WA-DED (Wire Arc Direct Energy Deposition), and the results were compared using statistical methods. Factors to capture manufacturing influence and buildup direction were statistically validated on 316L. The work shows a benchmark with a typical initial microstructure of rolled and milled material, L-PBF, and WA-DED parts on loads close to the application and thus simplifies an industry-oriented evaluation of a new manufacturing process.

Particle tracking in a simulated melt pool of laser powder bed fusion

Laser powder bed fusion (LPBF) is an additive manufacturing technique that prints objects layer-by-layer by selectively melting powders using a focused laser. The mechanical properties of LPBF parts are affected by processing parameters that influence the flow within the melt pool. Marangoni convection is a surface tension dependent mass transfer process from the region of lower surface tension to the region of higher surface tension, influenced by temperature and the presence of surface-active elements. The Marangoni convection-induced flow pattern in the molten metal pool can induce different surface characteristics and defects. Tracking the surface oxide particles in the melt pool can be a potential mechanism for assessing the properties of the fabricated parts. Therefore, in this work, a particle tracking algorithm was developed to track the surface oxide particles in a melt pool produced using LPBF. The flow patterns in the melt pool were observed using high-speed camera. Binary images of the melt pool were simulated using MATLAB script based on the experimental observations. The particle tracking algorithm was used for different flow patterns: radially outward, radially inward, and rotational. Various factors affecting the accuracy of the particle tracking algorithm were identified, such as melt pool size, image pixel size, size and number of surface oxides, flow pattern, and particle velocity. The image pixel size, number of surface oxides, and particle velocity were found to have maximum influence on the accuracy. The probability of error has been quantified, and the causes of errors have been explored.

In-situ monitoring plume, spattering behavior and revealing their relationship with melt flow in laser powder bed fusion of nickel-based superalloy

Laser powder bed fusion (LPBF) is a highly dynamic and complex physical process, and single-track defects tend to accumulate into non-negligible internal defects of parts. The nickel-based superalloy single track was fabricated by LPBF, and its plume and spattering behavior were monitored in situ and recorded in real time based on image recognition and tracking in this study. The relationship among laser energy density, melt flow, plume and spattering behavior during LPBF was discussed. Volumetric energy density had limitations as a design parameter for LPBF. However, we found that plume and spattering behavior can be used as real-time design parameters for the processing of LPBF parts and implemented the initial velocity statistics for LPBF single-track spattering based on the centroid extraction algorithm. The influence of melt flow evolution paths on the spattering and plume behavior in three different melting modes was revealed, and a shift in plume behavior was found in the overlap region of the additive substrate. This study provides a new method for obtaining statistics of spattering-related physical quantities in the melting mode, which is beneficial for the development of processing methods to mitigate the instability of the LPBF process.

Laser ultrasonic detection of submillimeter artificial holes in laser powder bed fusion manufactured alloys

In the development of additive manufacturing (AM) technology, laser powder bed fusion (LPBF) is one of the important processing methods. However, the hole defects in the fabricated samples limit the development. Laser ultrasonic (LU) technology plays a major role in the detection of LPBF parts with tiny defects, which has the advantages of non-contact and non-destructive. In this work, the detection of submillimeter internal defects in four typical LPBF alloys by LU technology is studied numerically and experimentally. A multiphysics simulation model of LU detection is established to investigate the propagation characteristics of excited ultrasonic waves in different LPBF alloys and their interaction with submillimeter artificial defects. Simulation results show that the amplitude of longitudinal (L) wave at the defect is the largest in AlSi10Mg alloy, and the amplitude of L wave in the 316L alloy, Ti6Al4V alloy and In718 alloy are very close, but their phases are slightly different. The amplitude of L wave tends to decrease nearly linearly with the increase in defect diameter. Then, four typical LPBF alloys are fabricated and measured by the LU through-transmission detection. The geometric information of artificial holes with a diameter larger than 0.2 mm are clearly characterized by the LU C-scan results, indicating the prominent applicability and feasibility of LU detection on different materials fabricated by LPBF.