Predictive Theoretical and Computational Approaches for Additive Manufacturing Proceedings of a Workshop (2016) / Chapter Skim
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6 Summary of Issues from Subgroup Discussions
6 Summary of Issues from Subgroup Discussions
Pages 103-118
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THEORETICAL UNDERSTANDING OF MATERIALS SCIENCE AND MECHANICS Subgroup Members Steve Daniewicz (Mississippi State University) , Marianne Francois (Los Alamos National Laboratory)
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, • Multiple simultaneous processes (e.g., heat, fluid, particle flow, phase changes, stress-strain including crystal plasticity) , and • Experimental material design utilizing information science.
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and finite element structural analysis codes already exist but more efficient, accurate, and robust numerical methods with implicit solvers would be useful, as would additional reduced-order models and computational techniques for multiscale methods. They also emphasized that models are needed for melt pool dynamics (e.g., interface tracking method with phase change)
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From page 106... ...
Several subgroup members identified what they viewed as the most important open questions in materials and mechanics, including related scientific disciplines, engineering and mathematics, as well as the technical challenges to be addressed for predictive theoretical and computational approaches in order to enable widespread adoption of AM. In doing so, they listed some areas of fundamental research in theoretical and computational materials science, mechanics, and multiscale computation that could advance AM: • Polymer FDM (P-FDM)
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From page 107... ...
• Linkage. Linking scales and models is also a challenge, including connecting phase change models through thermodynamic calcula tions and linking microstructure information to macroscale models. • Materials. Some subgroup participants emphasized that the future of AM eventually might be dominated by material questions because there are limitless ways of combining materials.
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From page 108... ...
This might include exploiting big data techniques to deepen the validation process, such as using reconstructed images and or diffraction data. They noted that there is a strong need for on-line in situ metrologies to be built in as standard on equipment (e.g., temperatures, molecular and microstructural information, microscopies)
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From page 109... ...
, equipment manufacturers, metrologists, computational and theoretical modelers, end users and developers, and standards bodies to increase communication and collaboration while accommodating the groups' various interests. In particular, they suggested potential focuses of partnerships, such as developing physics models and numerical methods, implementing models and methods in software, and performing validation.
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From page 110... ...
Specifically, some subgroup participants mentioned the need for a common test bed with multiple challenge problems to build confidence in simulations and AM builds, observing that AM-build benchmarks would be of great interest to the ASTM F42 Committee on Additive Manufacturing. They envisioned two classes of test problems: 1.
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From page 111... ...
A few subgroup members noted that standards organizations such as ASTM E08 and F42 work commonly with coupons, but simulations are needed to bridge the gap between coupons and components. Several subgroup members commented that workshop presentations repeatedly mentioned the various parameters describing melt pool solidification rate or heat input, which can be used to describe a successful build.
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From page 112... ...
Many participants stressed the value of integrating multidisciplinary optimization into a build, including topology, shape, material, manufacturing, uncertainty quantification, residual stress, build path, and feedback. They noted that advanced macroscale viscoplastic material models are also needed.
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From page 113... ...
Surrogate and reduced models derived from HPC models show promise for industrial use, especially those that focus on residual stress, prediction, control, and minimization. New models and software might have value, including advanced macroscale viscoplastic models with internal state variables capable of modeling processing history and new CAD representations for AM.
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From page 114... ...
However, they noted that several challenges were not discussed during the workshop, including the importance of the measurement matrix for different simulation tools and the fact that the closed nature of the machines makes it difficult to access the complete data history of machines. They also mentioned the challenges of testing and examining internal features of AM parts, such as identifying the voids in thin walls particularly when the tolerable pore size is just one order smaller than the feature size.
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further develop model-based reconstruction techniques for CT scan; (5) improve simulation tools for powder development; and (6)
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They noted that rapid simulations for in situ fine tuning of build parameters require a feedback loop with in situ process monitoring (e.g., temperature profile, melt pool width) , possibly after each layer is deposited.
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Other subgroup members noted that careful design of validation experiments for model validation, uncertainty quantification, and in situ process monitoring is challenging because there is a lack of data for probabilistic modeling and error estimation. Test standards and test artifacts would help, as would an adequate suite of in situ monitoring to provide useful engineering data, they explained.
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