添加剂制造的 Ti-6Al-4V 的相关 X 射线计算机断层扫描和光学显微镜序列切片数据

IF 2.4 3区 材料科学 Q3 ENGINEERING, MANUFACTURING
Bryce R. Jolley, Daniel M. Sparkman, Michael G. Chapman, Edwin J. Schwalbach, Michael D. Uchic
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引用次数: 0

摘要

通过 X 射线计算机断层扫描和光学显微镜连续切片对添加制造的钛合金样品进行了表征,以便对内部孔隙率进行相关分析。钛合金球轴承被粘附在圆柱形样品的表面,以帮助数据集的登记。表征数据包括来自四种不同仪器的五次 X 射线计算机断层扫描和光学显微镜连续切片图像。本文提供了收集这些多个数据集的方法和参数,以及每个数据集所选感兴趣体积的重建数据。此外,还提供了每次计算机断层扫描的原始投影数据。重点介绍了序列切片实验中的意外伪影,并讨论了这些伪影的潜在影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Correlative X-ray Computed Tomography and Optical Microscopy Serial Sectioning Data of Additive Manufactured Ti-6Al-4V

Correlative X-ray Computed Tomography and Optical Microscopy Serial Sectioning Data of Additive Manufactured Ti-6Al-4V

An additively manufactured titanium alloy sample has been characterized by X-ray computed tomography and optical microscopy serial sectioning to enable a correlative analysis of internal porosity. Titanium alloy ball bearings were adhered to the surface of the cylindrical sample to aid the registration of the datasets. The characterization data includes five X-ray computed tomography scans from four different instruments and optical microscopy serial sectioning images. The methods and parameters used for collecting these multiple datasets, and reconstructed data for each dataset‘s selected volume of interest are provided. Raw projection data from each computed tomography scan are also offered. Unanticipated artifacts within the serial sectioning experiment are highlighted, and the potential impact of these artifacts is discussed.

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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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