在 AM 2022 工作台内对裸镍合金 718 板材的激光轨迹进行特定位置微结构表征

IF 2.4 3区 材料科学 Q3 ENGINEERING, MANUFACTURING
L. E. Levine, M. E. Williams, M. R. Stoudt, J. S. Weaver, S. A. Young, D. Deisenroth, B. M. Lane
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引用次数: 0

摘要

金属合金的增材制造所产生的微观结构通常与传统制造方法所产生的微观结构大相径庭。计算机模拟有助于将这些材料的加工、结构和性能联系起来,但很难生成涵盖整个范围的验证数据。这项研究是增材制造基准测试系列广泛努力的一部分,目的是为镍合金 718 的激光粉末床熔融制造生成此类数据集。在此,我们使用光学显微镜、电子反向散射衍射和能量色散光谱仪,对在激光功率、扫描速度和激光直径变化的情况下产生的单条激光轨迹,以及在裸露的锻造合金 718 板上产生的相邻激光轨迹阵列进行了检查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Location-Specific Microstructure Characterization Within AM Bench 2022 Laser Tracks on Bare Nickel Alloy 718 Plates

Location-Specific Microstructure Characterization Within AM Bench 2022 Laser Tracks on Bare Nickel Alloy 718 Plates

Additive manufacturing of metal alloys produces microstructures that are typically very different from those produced by more traditional manufacturing approaches. Computer simulations are useful for connecting processing, structure, and performance for these materials, but validation data that span this full range is difficult to produce. This research is part of a broad effort by the Additive Manufacturing Benchmark Test Series to produce such datasets for laser powder bed fusion builds of nickel Alloy 718. Here, single laser tracks produced with variations in laser power, scan velocity, and laser diameter, and arrays of adjacent laser tracks on bare wrought Alloy 718 plates are examined using optical microscopy, electron backscatter diffraction, and energy dispersive spectroscopy.

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来源期刊
Integrating Materials and Manufacturing Innovation
Integrating Materials and Manufacturing Innovation Engineering-Industrial and Manufacturing Engineering
CiteScore
5.30
自引率
9.10%
发文量
42
审稿时长
39 days
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.
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