Additive Manufacturing: Processing Effects on Microstructure and Material Performance: Process Variables I
Sponsored by: TMS: Additive Manufacturing Committee
Program Organizers: Eric Lass, University of Tennessee-Knoxville; Joy Gockel, Wright State University; Emma White, DECHEMA Forschungsinstitut; Richard Fonda, Naval Research Laboratory; Monnamme Tlotleng, University of Johannesburg; Jayme Keist, Pennsylvania State University; Hang Yu, Virginia Polytechnic Institute And State University
Monday 8:00 AM
February 24, 2020
Room: 6E
Location: San Diego Convention Ctr
Session Chair: Eric Lass, The University of Tennessee, Knoxville; Joy Gockel, Wright State University
8:00 AM
Towards Accelerated Maturation of Additive Titanium Alloys: Soumya Nag1; Neil Johnson1; Lee Kerwin2; Yiming Zhang1; Sathyanarayanan Raghavan1; Sreekar Karnati1; Eric MacDonald3; Alex Kitt2; Changjie Sun1; Genghis Khan1; Chris Williams4; Thomas Broderick5; Mark Benedict5; Dave Siddle6; 1GE Research; 2EWI - Buffalo Manufacturing Works; 3Youngstown State University; 4GE Aviation; 5Air Force Research Laboratory; 6America Makes
Additive manufacturing modalities aligned with the AM Genome initiative are used to rapidly generate custom-designed builds for expedited processing-structure-property evaluation, also allowing for build flexibility and customization of parts. However, AM parts have to go through long iterative evaluation cycles, which greatly increases the time and cost of substantiating the process and component.In the current study, material system of choice is Ti64 – the workhorse alloy for structural aerospace and biomedical applications. Powder blown Directed Energy Deposition (DED) technique was employed to build common features that are critical for part performance. Build parameter DOEs were conducted to determine defect density and microstructural descriptors, and in turn relate them to material property values. Armed with this information, physics based predictive models were generated to develop response surfaces. Developing and validating such feature-based build qualification (FBQ) catalogues is a big step towards improving the process qualification of DED components.
8:20 AM
Process-structure-property Relationships for As-built Inconel 718 Thin Walls Manufactured with the Laser Powder Bed Fusion Process: Paul Paradise1; Mandar Shinde1; Sridhar Niverty1; Dhruv Bhate1; Nikhilesh Chawla1; 1Arizona State University
Among metal Additive Manufacturing (AM) processes, the Laser Powder Bed Fusion (LPBF) is well regarded for its ability to realize fine feature resolution on the order of hundreds of microns. A challenge to the implementation of these fine features in critical, functional parts such as heat exchangers, however, is that the mechanical properties at these scales have been shown to be inferior to their bulk counterparts. In this work, we examine the underlying reasons for this debit by studying the effects of LPBF process parameters on porosity and microstructure, and its subsequent effect on quasi-static mechanical properties. We show in particular that the laser scan strategy has a crucial role in influencing these properties. Using a combination of process DOEs, white light interferometry, micro-CT scanning, EBSD and mechanical testing, we develop process-structure-property relationships specific for thin walls between 0.30 and 2mm, made out of Inconel 718 using the LPBF process.
8:40 AM
Selection of Process Parameters for Controlling Microstructural Properties in Additive Manufacturing: A Machine Learning Based Approach: Sudeepta Mondal1; Daniel Gwynn1; Nandana Menon1; Asok Ray1; Amrita Basak1; 1Pennsylvania State University
During material consolidation in additive manufacturing (AM), the melt pool dimensions play a critical role in determining the final grain structure and thus the resulting mechanical properties. However, maintaining desired melt-pool properties are challenging due to the inherent layer-by-layer fabrication process resulting in cyclic heating and cooling as well as thermal gain of the component being built. As a possible solution to this problem, a physics-informed machine learning (ML) assisted modeling and optimization framework was explored in this work. An analytical heat transfer model is employed for predicting the thermal distribution in a directed energy deposition process for faster computation. Thereafter, a surrogate-assisted statistical learning and optimization architecture involving Gaussian Process-based modeling and Bayesian Optimization is employed for finding the optimal set of process parameters as the scan progresses, subject to the constraint of maintaining a desired percentage of columnar growth during the build.
9:00 AM
P-V Process Optimization for Microstructure Homogeneity and Cracking Control of SLM-fabricated H13 Tool Steel: Yining He1; Nicholas Jones1; Ming Zhong1; Bryan Webler1; Jack Beuth1; 1Carnegie Mellon Univ
H13 tool steel is a promising material for selective laser melting (SLM) fabrication. However, its part microstructure and crack susceptibility were significantly influenced by beam power (P) and scan speed (V). This dependence between processing, microstructure, and cracking was investigated in this study with single-tracks, multi-track pads, and 3D cubes, all produced by an EOS-M290 machine. Forty P-V combinations were selected for single-track fabrication. Inhomogeneities in microstructure were observed for some P-V combinations, with a transition from network-like structure to isolated whisker-like structure, often in the same melt pool. A processing map was developed to show expected microstructure inhomogeneity tendency for P-V parameters in different range. Eighteen multi-track pads fabricated by different P-V combinations showed higher cracking tendency for certain microstructure classes. P-V process windows of higher and lower cracking tendency were identified. Analysis of eight cubes printed in different P-V windows showed good correspondence with these tendencies.
9:20 AM Cancelled
Experimental and Numerical Studies on Melt Pools of Single Tracks Processed by Laser Powder Bed Fusion: Yoon Suk Choi1; Jaewoong Kim1; Seulbi Lee1; 1Pusan National University
The variation of melt pool geometries was investigated experimentally and numerically as a function of process parameters for single tracks of Alloy 718 processed by the laser powder bed fusion (PBF). The depth and width of melt pools were measured and related to PBF process parameters. The thermal analysis using finite element method (FEM) was performed to predict the width and depth of melt pools under different PBF process parameters. Here, the laser absorptivity and penetration depth of the heat-source model for the thermal FEM were set to vary to capture the depth and width of melt pools with different PBF process parameters. The resulting optimum variations of the laser absorptivity and penetration depth were found to be uniquely formulated as a function of a new energy density-related parameter, which is the liner energy density multiplied by the laser power. The detailed underlying physics was investigated and will be discussed.
9:40 AM Break
10:00 AM
Laser Beam Shaping for the Additive Manufacturing of Metal Components with Reduced Texture and Equiaxed Grains: Tien Roehling1; John Roehling1; Rongpei Shi1; Saad Khairallah1; Gabe Guss1; Joseph McKeown1; Manyalibo Matthews1; 1Lawrence Livermore National Laboratory
Gaussian beam intensity profiles are standard in laser-based metals additive manufacturing, although recent work has shown that beam shaping could offer a feasible route towards microstructural control, at least in single melt tracks. In this study, 316L stainless steel parts were built using Gaussian and elliptical laser intensity profiles under identical conditions. Cross-hatching was achieved with custom instrumentation that allows non-circular beams to be rotated between layers. Microstructural characterization was performed using electron backscatter diffraction (EBSD) imaging. Using elliptical beams, some refinement of the columnar and equiaxed grains is achieved, but more importantly, the volume fraction occupied by equiaxed grains increases dramatically such that the average grain size is reduced by nearly 50%. Moreover, almost no texture exists in cubes built using an elliptical beam, while cellular growth of columnar grains along a preferred direction was found in cubes built using a Gaussian beam.
10:20 AM
Tailoring Microstructure Through Beam Shaping: Saad Khairallah1; Rongpei Shi1; Tien Roehling1; Tae Wook Heo1; Joseph Mckeown1; Manyalibo Matthews1; 1Lawrence Livermore National Laboratory
Laser powder bed additive manufacturing is promising a new process capability, that of tailoring mechanical properties by locally controlling the microstructure. The thermal history produced in a raster scan already produces heterogeneous and spatially non-uniform structures and differ from conventional manufacturing. Understanding how these thermal profiles result in AM centric microstructure is crucial to controlling AM process parameters and final mechanical properties. We present a high-fidelity powder scale simulation model that is fully-coupled with cellular automata for grain growth. The model uses full laser ray tracing to accurately capture the thermal profiles imposed by different beam shapes at varied laser scan speeds. The model accounts for nucleation and epitaxial growth and shows that beam shaping is a strategy to control the columnar to equiaxed transition.Work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory contract DE- AC52-07NA27344. Lawrence Livermore National Security, LLC. LLNL-ABS-771760.
10:40 AM
A Comparison Between Multi-scale Area Analysis and ISO Surface Roughness Parameters for Characterizing Additively Manufactured Surfaces: Nathaniel Rutkowski1; Christopher Brown2; Sneha Narra2; 1Worcester Polytechnic Institute ; 2Worcester Polytechnic Institute
In this work, multiscale area analysis (MAA) and ISO surface roughness parameters (SRP) will be considered as metrics for characterizing surface topographies (ST) of AlSi10Mg and IN718 blocks produced by additive manufacturing (AM), particularly laser powder bed fusion (LPBF). The complex ST of LPBF parts is highly dictated by the deposition parameters, powder size, and morphology. It is unclear which SRP are relevant for analyzing AM parts. Test blocks were manufactured by systematically varying beam power, travel velocity, part thickness, and overlap between the contours. Preliminary results from MAA and ISO SRP have shown that the surface roughness of the part is correlated to the melt track dimensions and the ISO SRP correlations do not hold at smaller scales. Understanding the most relevant metrics to measure ST of AM parts can assist in the development of application-specific manufacturing standards.
11:00 AM
Origin of Dislocation Structures in Additively Manufactured Austenitic Stainless Steel: Kaila Bertsch1; Gabriel Meric de Bellefon1; Bailey Kuehl1; Dan Thoma1; 1University of Wisconsin-Madison
Additively manufactured (AM) stainless steels exhibit hierarchical, chemically inhomogeneous dislocation microstructures, but their exact origins are not fully understood. In this study, the physical origins of AM dislocation structures were investigated by isolating the effects of thermal distortions on the microstructure. “1D” rods, “2D” walls, and 3D geometries were fabricated with directed energy deposition (DED) and selective laser melting (SLM) of 316L such that thermal cooling and expansion were less constrained in parts with lower dimensions. The influences of dendritic segregation, misorientations between dendrites, and geometric constraints on dislocation structure formation were evaluated via SEM, transmission EBSD, S/TEM, and EDS. Dislocation density increased with increasing geometric constraints, increasing by an order of magnitude with each additional dimension in DED parts. Dislocations were found to originate due to thermal stresses, and the interaction between mobile dislocations and solute-rich interdendritic regions dictate the crystallography and scale of the final microstructure.