Applying computational thermodynamics to additive manufacturing
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Applying computational thermodynamics to additive manufacturing WHITE PAPER
A
Adam Hope and Paul Mason Thermo-Calc Software Inc.
dditive manufacturing of metals is one of the fastest growing sectors in the three-dimensional (3D) printing market. The potential for light-weighting, increased part complexity, reduced materials waste and labor, and the ability to introduce local changes in materials properties throughout the build have huge implications for how engineers design and manufacture parts. This is a disruptive technology, and many materials challenges remain to be addressed for additive manufacturing to reach its full potential. For example, many additive processes subject the material to rapid solidification with multiple subsequent reheat cycles, and the effects of thermal cycles on materials properties are sometimes unknown and typically do not result in the properties of a similar cast or wrought metal. Additionally, many additively manufactured parts are built using conventional alloys that have been engineered for cast or wrought processes. In some cases, these alloys are not suitable for additive processing, and problems such as deleterious phases forming during a postbuild stressrelief heat treatment, designed for conventionally treated alloys, may result. As our understanding of the metallurgy of these alloys under innovative and new processing conditions grows, new alloys could be designed that take advantage of the rapid solidification and numerous reheat cycles to promote a materials microstructure that leads to desirable mechanical properties. A report by the National Academies on integrated computational materials engineering (ICME)1 in 2008 outlined an approach to designing products, the materials they are comprised of, and their associated materials processing methods
by linking materials models at multiple length scales. The report highlighted the need for a better understanding of how processes produce materials structures, how those structures give rise to material properties, and how materials can be selected for a given application, describing the need for using multiscale materials modeling to capture the process-structures-properties-performance characteristics of a material. This is especially true in the case of additive manufacturing, where it is almost impossible to model the process without considering solidification, thermal cycling, and materials changes in an integrated fashion. Computational thermodynamics, specifically CALPHAD (CALculation of PHAse Diagrams),2 allows for the prediction of thermodynamic properties and phase stability of an alloy under stable and metastable conditions. The CALPHAD approach can also be extended to model atomic mobilities and diffusivities. By combining thermodynamic and mobility data, kinetic reactions during solidification and subsequent heat-treatment processes can be simulated. Computational thermodynamics and CALPHADbased tools are important components of an ICME framework. Through the use of such simulations, it is possible to vary allo
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