Lin Wang

Bio: Lin Wang is an academic researcher from Monash University, Clayton campus. The author has contributed to research in topics: Materials science & Fusion. The author has an hindex of 2, co-authored 6 publications receiving 31 citations. Previous affiliations of Lin Wang include Chinese Ministry of Education.

Numerical studies of melt pool and gas bubble dynamics in laser powder bed fusion process

Abstract: The formation of pores can severely deteriorate the quality of parts fabricated by laser powder bed fusion (LPBF) technology. However, how the pores formation relates to melt pool and gas bubble dynamics is still not well understood. Here, through the modeling of the metal powder melting and the subsequent solidification under the conduction mode, it was found that the molten liquid near the gas-liquid interface flows centrifugally and vortices including a clockwise and an anticlockwise vortex are produced. The anticlockwise vortex dominates the molten liquid when laser turns off. The motion of gas bubbles originating from the powder bed voids follows the melt pool flow synchronously, where bubbles can coalesce, and some escape from the top and sides of the melt pool, and some remain as pores in the solidified part. For the positive value of surface tension gradient, the centripetal Marangoni convection drives the melt pool to flow in the dual clockwise circulation and obstructs the escaping orbit of bubbles, leading to higher porosity and surface humping. The present study enhances the further understanding of multi-physics in LPBF process.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Influences of powder morphology and spreading parameters on the powder bed topography uniformity in powder bed fusion metal additive manufacturing

Abstract: Powder spreading is a crucial step in the powder bed fusion process, which controls the quality of powder bed and consequently affects the quality of printed parts. To date, however, powder spreadability has received very little attention and substantial fundamental work is still needed, largely because of the lack of experimental studies. Therefore, the focus of the present study addresses the influences of powder morphology, spreading velocity and layer thickness on the powder bed topography uniformity. The experiments were conducted with a laser powder bed fusion printer and the powder layers were spread systematically and comprehensively assessed. In summary, it was found that particle sphericity and surface texture dictates the degree of impact that the spreader velocity and the layer thickness exert on the quality of powder bed topography in spread layers. The spreader velocity has substantial influence on powder bed uniformity, such that better uniformity is achieved with low spreading velocities, ≤ 80 mm/s. Powders with a wide particle distribution and containing large number of fine particles (

Dynamic investigation on the powder spreading during selective laser melting additive manufacturing

Abstract: In selective laser melting in additive manufacturing, powder spreading significantly affects the subsequent operating procedure as well as the quality of final products. Compared with large amount of previous work on powder spreading on a flat substrate surface before printing, in this article, 3D particulate scale dynamic simulations were carried out to study the spreading of 316 L stainless steel powder during printing by using discrete element method (DEM). The influences of various factors including processing parameters, blade shape, and the powder size on the quality of the spread powder bed were investigated in terms of both macroscopic packing density/uniformity and microstructure/micro dynamics. And optimized condition was identified. The mechanisms were also analyzed based on the powder behavior and forces caused by cooperative interaction between the formed zone (printed part) and the already packed powder layer. The results show that the blade moving speed can seriously influence the quality of the spread powder bed; normally the smaller the blade moving speed, the higher the powder bed quality, but the lower the working efficiency. Therefore, through comprehensive consideration, the proper blade moving speed is chosen to be 0.1 m/s. Increasing the blade gap height or decreasing the particle size (i.e., D = 30 µm) will increase the average relative packing density and structure uniformity. The angle of 15° for the blade is proved to be optimal for excellent powder spreading. Through simulation under optimized parameters, it can be found that the spread powder layer can be more uniform and much denser with high efficiency. And both macroscopic and microscopic analyzes indicate that the spread powder bed has desired structure and property. These findings can improve the fundamental understanding on the powder spreading and provide valuable references for the formation of high quality powder bed during 3D printing.