Showing papers by "Yung C. Shin published in 2022"

Laser cladding of aluminum alloys with concurrent cryogenic quenching for improved microstructure and hardness

Abstract: In this study, a method to deposit quench-sensitive age-hardening aluminum alloy clads is presented, which produces a hardness similar to the T6 temper without the requirement of solution heat treatment. A high-powered diode laser is scanned across the workpiece surface and material feedstock is delivered and melted via off-axis powder injection. The cladding process is immediately followed by quenching with liquid nitrogen, which improves the cooling rate of the quench-sensitive material and increases the hardness response to subsequent precipitation heat treatment. The method was demonstrated on the laser cladding of aluminum alloy 6061 powder on 6061-T6511 extruded bar substrates of 12.7 mm thickness. Single-track single-layer clads were deposited at a laser power of 3746 W, scan speed of 5 mm/s, and powder feed rate of 18 g/min. The in-situ liquid nitrogen quenching improved the clad hardness by 15.7% from 73.1 HV to 84.6 HV and the heat-affected zone hardness by 19.3% from 87.1 HV to 103.9 HV. Extending the process to multi-track multi-layer cladding further increased the clad hardness to 89.3 HV, close to the T6 temper hardness of 90 HV. Transmission electron microscopy revealed the increased precipitate density in the liquid nitrogen quenched clads were responsible for the higher hardness.

Data-Driven Modeling of Mechanical Properties for 17-4 PH Stainless Steel Built by Additive Manufacturing

Abstract: This study examines the link between microstructure and mechanical properties of additively manufactured metal parts by developing a predictive model that can estimate properties such as ultimate tensile strength, yield strength, and elongation at fracture based upon microstructural data for 17-4 PH stainless steel. The main benefit of the approach presented is the generalizability, as necessary testing is further reduced in comparison with similar methods that generate full process–structure–property linkages. Data were collected from the available literature on AM-built 17-4 PH stainless steel, in-house tensile testing and imaging, and testing conducted by an AM company. After standardizing the image size and grain boundary extraction via image processing, the features such as grain size distributions and aspect ratios were extracted. By using artificial neural networks, relationships were established between grain size and shape features and corresponding mechanical properties, and subsequently, properties were predicted for novel samples to which the network had not previously been exposed. The model produced correlation coefficients of R2 = 0.957 for ultimate tensile strength, R2 = 0.939 for yield strength, and R2 = 0.931 for fracture elongation. These results demonstrate the efficacy of predictive models that focus upon microstructure–property relationships and highlight an opportunity for further exploration as predictive modeling of metal additive manufacturing continues to improve.

Analysis of the Heat-Affected Zone and Ablation Efficiency in Terms of Burst Mode Parameters During High Power Picosecond Laser Micromachining of Metals

Abstract: The past decade has seen a significantly increased use of high-power ultrafast lasers in micromachining applications. With the continual increase of the laser power for ultrafast lasers, an increase in the ablation rate has been brought about. However, it also created some negative effects, such as the heat-affected zone (HAZ) and thermal damages, which hardly occur at lower power. This issue was reported in the literature but has not been systematically addressed by previous research. This paper presents a systematic study on using the burst mode ablation to limit the HAZ while maintaining a high ablation efficiency using a high-power industrial picosecond laser with burst fluence larger than 10 J/cm2. An extended three-dimensional two-temperature model (3D-TTM) was employed to study the mechanism of the HAZ development and to predict the ablation efficiency with experimental validation. The essentiality of including the lattice heat conduction to predict accurate HAZ was discussed. The effect of the number of pulses per burst and pulse to pulse separation time was investigated. The optimal number of pulses per burst was obtained by using the 3D-TTM for copper and stainless steel. The 3D-TTM suggested that by using the optimal number of pulses per burst, a maximum reduction of 77% and 61% in HAZ could be achieved for copper and stainless steel respectively. And the corresponding ablation efficiency will be increased by 24% and 163% for copper and stainless steel at the same time. This study showed that burst mode laser machining at high fluence is an effective way of increasing efficiency while limiting the HAZ.