Newell Moser, Jake Benzing, Orion L. Kafka, Jordan Weaver, Nicholas Derimow, Ross Rentz, Nikolas Hrabe
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引用次数: 0
Abstract
The additive manufacturing benchmarking challenge described in this work was aimed at the prediction of average stress–strain properties for tensile specimens that were excised from blocks of non-heat-treated IN625 manufactured by laser powder bed fusion. Two different laser scan strategies were considered: an X-only raster and an XY raster, which involved a 90\(^\circ \) rotation in the scan direction between subsequent layers. To measure anisotropy, multiple tensile orientations with respect to the build direction were investigated (e.g., parallel, perpendicular, and intervals in between). Benchmark participants were provided grain structure information via electron backscatter diffraction measurements, as well as the stress–strain response for tensile specimens manufactured parallel to the build direction and produced by the XY scan strategy. Then, participants were asked to predict tensile properties, like the ultimate tensile strength, for the remaining specimens and orientations. Interestingly, the measured mechanical properties did not vary linearly as a function of tensile orientation. Moreover, specimens manufactured with the XY scan strategy exhibited greater yield strength than those corresponding to the X-only scan strategy, regardless of orientation. The benchmark data have been made publicly available for anyone that is interested [1]. For the modeling aspect of the challenge, five teams participated in this benchmark. While most of the models incorporated a crystal plasticity framework, one team chose to use a more semiempirical approach and to great success. However, no team excelled at all the predictions, and all teams were seemingly challenged with the predictions associated with the X-only scan strategy.
期刊介绍:
The journal will publish: Research that supports building a model-based definition of materials and processes that is compatible with model-based engineering design processes and multidisciplinary design optimization; Descriptions of novel experimental or computational tools or data analysis techniques, and their application, that are to be used for ICME; Best practices in verification and validation of computational tools, sensitivity analysis, uncertainty quantification, and data management, as well as standards and protocols for software integration and exchange of data; In-depth descriptions of data, databases, and database tools; Detailed case studies on efforts, and their impact, that integrate experiment and computation to solve an enduring engineering problem in materials and manufacturing.