流离失所(心理学)
断层摄影术
计算机断层摄影术
比例(比率)
原位
X射线
材料科学
拉伤
光学
物理
放射科
医学
心理学
解剖
气象学
心理治疗师
量子力学
作者
Orion L. Kafka,Alexander K. Landauer,Jake T. Benzing,Newell Moser,Elisabeth Mansfield,Edward J. Garboczi
标识
DOI:10.1007/s40799-024-00715-y
摘要
Abstract Purpose : Establish a technique for simultaneous interrupted volumetric imaging of internal structure and time-resolved full-field surface strain measurements during in-situ X-ray micro-computed tomography (XCT) experiments. This enables in-situ testing of stiff materials with large forces relative to the compliance of the in-situ load frame, which might exhibit localization (e.g., necking, compaction banding) and other inhomogeneous behaviors. Methods : The system utilizes a combination of in-situ XCT, 2D X-ray imaging, and particle tracking to conduct volumetric imaging of the internal structure of a specimen with interrupted loading and surface strain mapping during loading. Critically, prior to the laboratory-scale XCT experiments, specimens are speckled with a high-X-ray-contrast powder that is bonded the surface. During in-situ loading, the XCT system is programmed to capture sequential 2D X-ray images orthogonal to the speckled specimen surface. A single particle tracking (SPT) or digital image correlation (DIC) algorithm is used to measure full-field surface strain evolution throughout the time-sequence of images. At specified crosshead displacements, the motion and 2D image sequence is paused for volumetric XCT image collection. Results : We show example results on a micro-tensile demonstration specimen additive manufactured from Inconel 718 nickel-chrome alloy. Results include XCT volume reconstructions, crosshead-based engineering stress, and full-field strain maps. Conclusion : We demonstrate an in-situ technique to obtain surface strain evolution during laboratory-scale XCT testing and interrupted volumetric imaging. This allows closer investigation of, for example, the effect of micro-pores on the strain localization behavior of additive manufactured metal alloys. In addition to describing the method using a representative test piece, the dataset and code are published as open-source resources for the community. Graphical abstract
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