Additive Manufacturing Modeling and Simulation: Microstructure, Mechanics, and Process: AM Modeling - Microstructures & Defects
Sponsored by: TMS Computational Materials Science and Engineering Committee
Program Organizers: Jing Zhang, Purdue University in Indianapolis; Brandon McWilliams, US Army Research Laboratory; Li Ma, Johns Hopkins University Applied Physics Laboratory; Yeon-Gil Jung, Korea Institute of Ceramic Engineering & Technology
Monday 8:00 AM
October 18, 2021
Room: A113
Location: Greater Columbus Convention Center
Session Chair: Jing Zhang, Indiana University - Purdue University Indianapolis; Brandon McWilliams, CCDC Army Research Laboratory; Li Ma, Johns Hopkins University Applied Physics Laboratory; Yeon-Gil Jung, Changwon National University
8:00 AM
Spattering and Associated Pore Formation Modeling for Laser Powder Bed Fusion of Inconel 718: Qian Chen1; chaitanya Vallabh1; Albert To1; Xiayun Zhao1; 1University of Pittsburgh
Laser powder bed fusion (L-PBF) is an important additive manufacturing technology which allows the direct fabrication of metal parts with intricate internal structure in a layer-by-layer manner. Despite the wide industrial applications, L-PBF process still suffers a variety of issues in the fabricated part quality of which defect related to porosity is one of the issues not well studied and tackled. In this study, a spattering simulation model based on discrete element method (DEM) is unidirectionally coupled with single-track laser welding simulation to study the particle spattering driven by vapor flow. This DEM spattering model is calibrated by in-situ monitoring video through the directions and velocity of spattering particles. The landing process of mass particles the velocity of which is from DEM spattering model, is coupled with laser welding simulation to simulate the pore formation due to spattering particles landing on powder bed or entering in unsolidified melt pool.
8:20 AM
Mitigating Stray Grain Nucleation during the Laser Powder Bed Fusion of Single Crystal CMSX-4: Runbo Jiang1; Zhongshu Ren2; Tao Sun2; Anthony Rollett1; 1Carnegie Mellon University; 2University of Virginia
Even though the as-built microstructure of Laser Powder Bed Fusion parts is dominated by epitaxial grain growth continuing across the individual layers, stray grains frequently occur in laser melting of single crystals. The presence of these stray grains inserts grain boundaries and degrades high temperature properties. Within the current work, laser processing parameters were varied and stray grains were characterized within individual melt tracks in single crystal CMSX-4. Solidification and fluid flow modeling was performed using Flow-3D Computational Fluid Dynamics (CFD) to predict locations where nucleation has the highest probability to occur in the melt pool. Electron backscatter diffraction (EBSD) mapping was used to calibrate the CFD simulation and provides important information on stray grain area fraction and spatial distribution in the melt pool. It was found that compact melt pools with nearly semi-circular cross-sections are the least likely to exhibit stray grains.
8:40 AM
Cellular Automaton Simulation of Three-dimensional Microstructure Evolution during Powder Bed Fusion Additive Manufacturing: Michael Moodispaw1; Cheng Gu1; Alan Luo1; Qigui Wang2; 1Ohio State University; 2General Motors
Solidification microstructures determine the mechanical properties of powder bed fusion (PBF) additive manufacturing (AM) products, but evolution of the microstructure during the AM process is not well understood. A three-dimensional (3-D) cellular automaton (CA) model was developed to predict microstructures of metallic alloys during PBF additive process. In this model, undercooling was considered as the driving force for nucleation and grain growth, but both cooling rate and temperature gradient of the melt pool influenced grain nucleation and growth. Both 3-D and 2-D multi-layer simulations were performed as a comparison, and grain growth was not limited to a 2-D plane in the 3-D simulations. Overlap layers between adjacent layers during AM process were considered in the model. Earlier layers will experience more thermal cycles which will affect the final microstructure in the finished part. The simulation results were compared with PBF experiments of aluminum alloys, showing good agreement.
9:00 AM
A Computational Approach for Establishing Microstructure-property Relationships for Additively Manufactured IN718: An Nguyen1; Jason Mayeur1; 1The University of Alabama in Huntsville
Through layer-by-layer material deposition, Additive Manufacturing (AM) technology has allowed for direct creation of highly complex components. However, the presence of significant microstructural heterogeneity in AM materials has led to a need for different qualification requirements relative to conventionally produced wrought or cast material. The current approach to AM qualification and testing involves physical production of parts and mechanical testing for each manufacturing and post-processing methodologies, which is costly and time consuming. In this study, we use image-based grain scale polycrystalline simulations to explore material anisotropy, calibrate macroscale yield surface, explore spatial variation, and estimate effective properties of the Ni-based superalloy Inconel 718 produced by Laser-Power Bed Fusion. The simulated microstructures are statistically equivalent to sample material that has been characterized by Electron Back-Scattered Diffraction.
9:20 AM
A Microstructure-informed Multiscale Computational Model for Additively Manufactured (AM) Metals and Alloys: Chamara Herath1; Ajit Achuthan1; 1Clarkson University
The development of a multiscale computational modeling framework with a microstructure informed constitutive model and its implementation for additively manufactured materials with cellular sub-grain feature will be presented. The constitutive model is crystal plasticity based and accounts for the geometric and mechanistic effects of the grains and the cellular sub-grain feature. The cellular sub-grain feature is treated as tubular structures with hexagonal cross sections and grains are treated as columnar along the build direction. A multiscale homogenization of the local field quantities using generalized method of cells (GMC) micromechanics model is the crux of the framework. The GMC that captures the mechanical behavior of representative volume elements is linked to the macroscale Finite Element Analysis (FEA) model of the real-life-sized component using a Finite Element Analysis-Micromechanics Analysis Code (FEAMAC). The developed multiscale model is implemented on Calculix after integrating GMC and validated by simulating the performance of an aero-space component.
9:40 AM
Multiscale Material Modeling of Laser Powder Bed Fusion Additive Manufacturing Soft Magnetic Composites: Li Ma1; Caleb Andrew2; Ryan Carter1; Ian McCue1; Joe Sopcisak1; Mitra Taheri2; 1Johns Hopkins University Applied Physics Laboratory; 2Johns Hopkins University
Soft magnetic composites (SMCs) which provide high electrical resistivity with high magnetic permeability have the potential to create lighter and more efficient electronic devices. With the increasing complexity of the devices, conventional manufacturing methods limited their application. Recent advances in multi-material Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) have enabled the production of more complex SMCs. Our prior research has demonstrated that the as-built L-PBF sample with multi-material system incorporating NiZnCu-ferrite and high purity iron showed high maximum relative permeability. However, it is challenge to produce fully dense SMCs without defects.To improve the magnetic properties and reduce defects within the multi-material system, we develop the multiscale material modeling of L-PBF NiZnCu-ferrite soft magnetic composites. Mean field homogenization method is applied for two material system. The effect of various composition and scanning parameters on the melting pool size is studied. The computational results are compared with L-PBF experimental results.
10:20 AM Break
10:40 AM
CFD Simulations for Additive Manufacturing: Pareekshith Allu1; 1Flow Science Inc.
Computational fluid dynamics (CFD) simulations are a useful tool for optimization of process parameters in additive manufacturing processes such as laser powder bed fusion and directed energy deposition. CFD models, which are based on a rigorous solution of the conservation equations can provide further insights into fluid convection in the melt pool, porosity formation, temperature gradients, cooling rates and microstructure predictions. With experimental studies capturing melt pool temperatures and dimensions, it is possible to validate the numerical models that incorporate physics such as viscous flows, heat transfer, recoil pressure, phase change, and solidification. In this presentation, case studies from industry and academia highlighting the successful use of CFD models in understanding the influence of process parameters such as laser power, beam shape and scan speeds on AM process stability are discussed. Furthermore, information from these CFD models can be used to accurately model additional aspects like residual stresses and distortions.
11:00 AM
Comparison of Commercial Additive Manufacturing Simulation Tools for Full Build Analysis: Adam Gershen1; Charles Fisher1; 1Naval Surface Warfare Center, Carderock Division
Additive manufacturing (AM) is rapidly expanding due to its potential for design freedom, reduced material usage, and shorter lead time for replacement parts. However, build failures are frequent, and the process to decouple the root causes of error by physical means is costly and time intensive. Alternatively, modeling and simulation (M&S) can provide scientific insight of full builds’ residual stress and distortion evolution. The Navy is highly interested in advancing M&S practices to increase efficiency of AM design and fabrication. A continuation of ongoing programs, this study has focused on analyzing and comparing the small but growing set of commercially available AM simulation codes. In particular, this talk will dive deeper into numerous finite element analysis (FEA) computational tools for full-build analysis of the laser powder-bed fusion (L-PBF) process. The results will provide Navy personnel with the tools they need to accurately predict L-PBF builds and therefore minimize build failures.