Leila Ladani

Bio: Leila Ladani is an academic researcher from Arizona State University. The author has contributed to research in topics: Grain size & Nanoindentation. The author has an hindex of 22, co-authored 98 publications receiving 1436 citations. Previous affiliations of Leila Ladani include Utah State University & University of Texas at Austin.

Optimizing Quality of Additively Manufactured Inconel 718 Using Powder Bed Laser Melting Process

Abstract: Inconel 718, a widely used nickel based super alloy, is of special interest to the aerospace and automotive fields for its highly desirable and consistent material properties over a large range of temperatures. The objective of this research is to understand the effect of process parameters of a Direct Metal Laser Sintering (DMLS) machine, concerning mainly beam power between 40 W and 300 W and scan line speed between 200 mm/s and 2500 mm/s on scan line quality, line geometry and dimensions, and melt pool geometry in laser melted Inconel 718 line scans. A beam power that is too low (40 W) does not provide enough energy to maintain a continuous line. It was shown that mid-range beam powers (100 W and 150 W) result in the best and most uniform scan lines with minimal voids and shallower melt volumes. Higher power runs resulted in voids forming in the bottom of the melt pool and were consistent with either electron beam welding or melting processes operating at higher temperatures. Laser energy density (LED), a method of correlating the effects of scan speed and beam power into one characteristic process parameter, was also investigated. This ratio of beam power to scan speed follows a second order polynomial trend line for melt pool width and a logarithmic trend for average line width. LED values for melt pool depth are separated to show two trend lines as two mechanisms operate at low values below 0.25 J/mm and high values above 0.25 J/mm. LED values above 0.21 J/mm are desired for a continuous fill percentage in the formed lines, however dimensional accuracy of the line is sacrificed significantly at values over 0.2 J/mm.

Temperature distribution and melt geometry in laser and electron-beam melting processes – A comparison among common materials

Abstract: Due to the relative youth of metallic powder bed additive manufacturing technologies and difficulties with monitoring the process in situ, there is little consensus in the user community on how to optimize user variable parameters to ensure the highest quality and most cost effective build. Temperature distribution is the critical factor that dictates melting, microstructure and eventually the final part quality. Monitoring or measuring the temperature during the process is extremely difficult due to the ultra-high speeds and microscale size of the laser or electron beam. Therefore, other tools such as finite element modeling can be utilized to optimize these processes and predict the behavior of the system for different materials. This research presents transient, dynamic finite element model of the build process for both laser and electron beam melting techniques. The model includes melting and solidification of the powder as well as different thermal aspects such as conduction and radiation. Diffusivity of the powder is modeled and phase change is modeled such that latent heat of fusion is considered. Melt pool geometry and temperature distribution was obtained for different heat sources and different materials such as Ti6Al4V, Stainless Steel 316, and 7075 Aluminum powders. It was determined that heat accumulation is most consolidated within titanium powder beds, with steel being the second most consolidated, and aluminum powder beds having the most heat dissipation. As a result, titanium was seen to exhibit the highest local temperatures and largest melt pools, followed by steel and aluminum in decreasing order. Naturally, laser models showed smaller melt pool sizes and depths due to lower power. The beam speed and power used for Ti were found inadequate for creating a sustained and continuous melting of Al and Steel. Therefore, adjustments were made to these parameters and presented in this research.

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.

Display screen or portion thereof with graphical user interface

Abstract: Newness and distinctiveness is claimed in the features of ornamentation as shown inside the broken line circle in the accompanying representation.