“…From the models, the number of detected pores was lower than expected compared with the Archimedes in Table 4. Similar findings were reported by Promoppatum et al [28] in their study on pore detection using Micro-CT. The limited detection of pores was attributed to the detection capability of the Micro-CT which depended on the voxel size determined by the size of the specimen and the capacity of the machine.…”
Section: Density and Pore Characteristicssupporting
There is a concern regarding sub-surface pores within laser powder bed fusion of Ti-6Al-4V, which can initiate cracks and reduce mechanical properties, especially after machining for surface finishing. This study investigated the effect of laser scanning speed and fine shot peening on the pore characteristics, hardness, and residual stress of Ti-6Al-4V fabricated by laser powder bed fusion using scanning electron microscopy, X-ray micro-computed tomography, Vickers hardness, and X-ray diffraction. As the laser scanning speed increased, the number of pores and pore size increased, which reduced the hardness of Ti-6Al-4V. Most pores were less than 20 µm in size and randomly distributed. The fine shot peening generated plastic deformation and compressive residual stress on the surface, leading to higher hardness, with similar surface properties at all scanning speeds. The depth of compressive residual stress by fine shot peening varied corresponding to the scanning speeds. Increasing the scanning speed accelerated the rate of conversion between the compressive and tensile residual stresses, and decreased the depth of the maximum hardness by the fine shot peening from initial tensile residual stress within Ti-6Al-4V fabricated by laser powder bed fusion, thus reducing the enhancement achieved by the fine shot peening.
“…From the models, the number of detected pores was lower than expected compared with the Archimedes in Table 4. Similar findings were reported by Promoppatum et al [28] in their study on pore detection using Micro-CT. The limited detection of pores was attributed to the detection capability of the Micro-CT which depended on the voxel size determined by the size of the specimen and the capacity of the machine.…”
Section: Density and Pore Characteristicssupporting
There is a concern regarding sub-surface pores within laser powder bed fusion of Ti-6Al-4V, which can initiate cracks and reduce mechanical properties, especially after machining for surface finishing. This study investigated the effect of laser scanning speed and fine shot peening on the pore characteristics, hardness, and residual stress of Ti-6Al-4V fabricated by laser powder bed fusion using scanning electron microscopy, X-ray micro-computed tomography, Vickers hardness, and X-ray diffraction. As the laser scanning speed increased, the number of pores and pore size increased, which reduced the hardness of Ti-6Al-4V. Most pores were less than 20 µm in size and randomly distributed. The fine shot peening generated plastic deformation and compressive residual stress on the surface, leading to higher hardness, with similar surface properties at all scanning speeds. The depth of compressive residual stress by fine shot peening varied corresponding to the scanning speeds. Increasing the scanning speed accelerated the rate of conversion between the compressive and tensile residual stresses, and decreased the depth of the maximum hardness by the fine shot peening from initial tensile residual stress within Ti-6Al-4V fabricated by laser powder bed fusion, thus reducing the enhancement achieved by the fine shot peening.
“…The micrograph method, as described by Promoppatumet al. [21]. (2021) was applied to determine the mean LOF and melt pool dimensions, and the final volume of LOFs.…”
Section: Methodsmentioning
confidence: 99%
“…The powder material properties are shown in Figure 2. Figure 2 Material properties: thermal conductivity [19] and heat capacity [20] (a); density and viscosity [19] (b); heat transfer coefficient [19] and CTE [21] (c).…”
Despite the emerging research, it is still troublesome to control the defect formation in selective laser melted parts. In this paper, a mechano-thermo-fluid dynamical FEM model at meso-scale was proposed. The model calculates and predicts the volume and dimensions of lack-of-fusion (LOF) defects according to the applied process parameters. The numerical model was validated with experimentally assessed volume of lack-of-fusion defects and melt pool dimensions. Results shown the lowest volume of LOF defects (0.41%) in specimen produced with 275 W and scanning speed of 400 mm/s. Laser power was determined as a parameter majorly impacting the volume and dimensions of LOF in selective laser melted parts.
“…Though AM is a promising manufacturing technology, it is facing numerous challenges in printed part qualification and certification in aerospace, automotive, and biomedical engineering applications. Inherent process variabilities and uncertainties in processing parameters (e.g., laser scan speed, power, and spot diameter) lead to numerous manufacturing defects such as cracking 6 , porosity 7,8 , roughness 9,10 , balling 11 , inclusion 12 , and bead-up 13 . Combined efforts from academia, industry, and government organizations sought to fully realize the potential of AM technology through a better understanding of the process-structure-performance of the AM materials systems.…”
Challenge 3 of the 2022 NIST additive manufacturing benchmark (AM Bench) experiments asked modelers to submit predictions for solid cooling rate, liquid cooling rate, time above melt, and melt pool geometry for single and multiple track laser powder bed fusion process using moving lasers. An in-house developed Additive Manufacturing Computational Fluid Dynamics code (AM-CFD) combined with a cylindrical heat source is implemented to accurately predict these experiments. Heuristic heat source calibration is proposed relating volumetric energy density (ψ) based on experiments available in the literature. The parameters of the heat source of the computational model are initially calibrated based on a Higher Order Proper Generalized Decomposition- (HOPGD) based surrogate model. The prediction using the calibrated heat source agrees quantitatively with NIST measurements for different process conditions (laser spot diameter, laser power, and scan speed). A scaling law based on keyhole formation is also utilized in calibrating the parameters of the cylindrical heat source and predicting the challenge experiments. In addition, an improvement on the heat source model is proposed to relate the Volumetric Energy Density (VEDσ) to the melt pool aspect ratio. The model shows further improvement in the prediction of the experimental measurements for the melt pool, including cases at higher VEDσ. Overall, it is concluded that the appropriate selection of laser heat source parameterization scheme along with the heat source model is crucial in the accurate prediction of melt pool geometry and thermal measurements while bypassing the expensive computational simulations that consider increased physics equations.
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