Predictive Theoretical and Computational Approaches for Additive Manufacturing Proceedings of a Workshop (2016) / Chapter Skim
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2 Theoretical Understanding of Materials Science and Mechanics
2 Theoretical Understanding of Materials Science and Mechanics
Pages 5-32
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From page 5... ...
This includes but is not limited to design of metallic alloys or polymer blends, mixing and compatibilities of fundamental materials, heat source interaction with feedstock, heat source modeling, and incorporation of thermodynamic modeling into micro and macro heat transfer for the prediction of microstructures and metrology. Emphasis was placed on polymers, alloys, and alloy-polymer interfaces.
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TOWARD MODELING AND SIMULATIONS OF ADDITIVE MANUFACTURING OF METALS AT LOS ALAMOS NATIONAL LABORATORY Marianne Francois, Los Alamos National Laboratory Marianne Francois provided an overview of collaborative 1 efforts in modeling and simulation of AM at Los Alamos National Laboratory (LANL) , which largely focus on metals and directed energy deposition processes.
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From page 7... ...
The underlying material microstructures can dramatically impact material performance, as shown in Figure 2-1, Francois explained. In this figure, three microstructures of 316L stainless steel material are shown, where each varies due to processing differences (the material shown on the left was processed using AM, the middle was processed with the wrought method, and the right was processed using AM with a recrystallization heat treatment)
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This three-dimensional multiphysics package can model fluid flow with interface tracking and surface tension, heat transfer with phase change, species diffusion, and chemical reaction and solid mechanics. It also allows for complex geometries.
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The capabilities are being assessed via testing on AM process problems involving heat transfer and phase change, melt pool fluid flow (Marangoni effect) , and residual stress and distortion.
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Strength differences between wrought stainless steel and AM with recrystallization showed that the AM-processed materials have a smaller mean grain size, which generally increases strength in materials. Francois explained that researchers are currently studying whether the grain size difference is in part responsible for an observed strength difference between these manufacturing processes.
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. CHALLENGES IN ADDITIVE MANUFACTURING OF SOFT MATERIALS: POLYMER-BASED FUSED DEPOSITION MODELING Peter Olmsted, Georgetown University AM for soft materials is currently being examined through a joint project between researchers at Georgetown University6 and the National Institute of Standards and Technology (NIST)
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In the case of crystalline materials, when the polymer is extruded out of the nozzle, it leaves an oriented polymer filament that is more likely to crystallize. Therefore, the crystalline morphology reflects the properties of the processing and impacts the mechanical properties.
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In particular, understanding the molecular shape, structure, orientation, and alignment through the filament at the center and the edges is essential to understanding the flow through the filament. This needs to be coupled to the changing temperature field, the non-Newtonian fluid mechanics, the density changes, the moving and changing boundaries between solid surfaces and free surfaces, and, if crystallinity is involved, the effects of phase change materials on latent heat and time scales.
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Olmsted noted the work of the Materials Genome Initiative (MGI) at NIST, which aims to develop a predictive materials database for AM; to predict mechanical properties, prototype speed, resolution, and processing parameters based on polymeric properties; to develop a seamless link between advanced metrologies, computation and prediction, and materials properties; and to shorten times for development of new protocols and products.
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• Open questions in materials and mechanics include the glass tran sition, flow-induced crystallization, and the relation of polymer molecular structure to fracture strength and deformation. • Unique fundamental research for AM includes the glass transition, polymer dynamics, interfaces, and other areas.
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large melt pool technologies, including plasma, e-beam, and laser using wire feedstock; and (2) powder-bed technologies, including laser and e-beam using powder feedstock.
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Then, the discrete element model with the multiphase code MFiX11 can be used to model particles melting and shrinking due to applied heat source. Phase field simulations are used to understand microstructural evolution.
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. Turner summarized that this research relies on multiple physics (e.g., conduction, convection, thermal radiation, solid-solid phase transformations, melting and solidification, fluid flow with surface tension, and solid mechanics)
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DISCUSSION Following their presentations, Marianne Francois, Peter Olmsted, and John Turner all participated in a panel discussion moderated by the workshop chair Wing Kam Liu from Northwestern University. The first question was posed by a virtual participant regarding how the different modeling stages are linked, given that there can be a strong interaction between these stages in relation to the material modeling.
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Francois agreed, noting that the underlying physics modeled (e.g., heat transfer with phase change, fluid flow) are similar but the differences (e.g., mass and energy deposition)
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In conclusion, Liu emphasized that clarifying these processes would help encourage university-industry-government partnerships. THEORETICAL UNDERSTANDING OF MATERIALS SCIENCE AND MECHANICS Steve Daniewicz, Mississippi State University Steve Daniewicz explained that his presentation would focus on two of the overarching session questions: What multidisciplinary and related materials and mechanical sciences are needed for AM?
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From page 22... ...
Porosity, mechanical failure, residual stress and corresponding distortion, and fatigue are issues to be considered. There are several multidisciplinary scientific needs, as described by Daniewicz: • Powder-heat source interactions, • Microstructure evolution under non-equilibrium conditions, • Heat transfer in melt pool and heat-affected zone, • Origins of metallographic texture, • Elastic-plastic constitutive relationships, • Residual stress and distortion prediction, • Melt pool solidification, and • Physics of porosity development.
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, according to Daniewicz. Understanding how thermal gradients produce residual stresses and subsequent distortion in additive parts is an ongoing research area.
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PART-LEVEL FINITE ELEMENT SIMULATION OF SELECTIVE LASER MELTING Neil Hodge, Lawrence Livermore National Laboratory Neil Hodge began by stating that there is great potential for selective laser melting (SLM) AM, but many significant challenges exist.
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started trying to develop models for SLM, they began with LLNL's Diablo code, which is a highly parallelized, implicit finite element code that can solve classical balance laws for solid mechanics (e.g., balance of thermal energy, balance of linear momentum) and associated thermal moving boundary problems.
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Hodge responded that the thermal gradients are the largest contributor to the residual stresses. Using this code, Hodge and his collaborators were able to examine other characteristics of SLM, including the complex thermal evolution.
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Other options may be to further explore physics-dependent time integration (e.g., time stepping) , physics- and spatially-dependent ynamics, improvement d of the phase change algorithm, discretization methods to handle geometry and multiple scales including contact (e.g., between part and baseplate)
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To enhance this understanding, Khairallah and his collaborators developed a mesoscopic three-dimensional simulation of metal powder-bed fusion using the LLNL code ALE3D.16 He showed simulation results of a laser traversing a stainless steel powder bed, with a strong melt flow and indications of incomplete melting. From this simulation, he framed his presentation into three key areas: 1.
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DISCUSSION Neil Hodge, Steve Daniewicz, and Saad Khairallah participated in a panel discussion following their presentations, moderated by Wing Kam Liu. An audience member posed the first question to Khairallah about the numerical methods used for the simulation he described (i.e., mesh strategies, time integration, spatial resolution, and governing equations)
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The participant responded that the physics community is developing similar physics-based models and there might be some opportunities to link these communities. A participant asked Khairallah if the powder distribution in the ALE3D simulation was uniform and if a distribution of powder sizes would impact cavity generation.
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could speed up calculations, Hodge stated that solving linear algebra is a hindrance for implicit finite element simulations. He has not seen any cases of highly parallelized linear algebra solvers on GPUs and suspects this will continue to be an issue until the linear algebra packages are updated to run on GPUs.
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