Data

Microstructure of a Commercial 316L Stainless-Steel Sample

Commonwealth Scientific and Industrial Research Organisation
Yang, Sam ; Wang, Haipeng ; Wang, Jinxiu ; Wang, Runhua ; Li, Jianli ; Liu, Rui
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/6hhb-7w51&rft.title=Microstructure of a Commercial 316L Stainless-Steel Sample&rft.identifier=10.25919/6hhb-7w51&rft.publisher=Commonwealth Scientific and Industrial Research Organisation (CSIRO)&rft.description=The sample used in this study was a commercial 316Lstainless-steel bar. The X-ray CT specimen was machined to a cylindrical shape with a length of 1cm and diameter of 2mm. The sample surface was polished by hand with a sandpaper. The X-ray projection images of the specimen was acquired using a Sanying Precision Engineering nanoVoxel-3000H microfocus X-ray CT machine. The CT slices have been analyzed using the DCM software.The X-ray projection images of the specimen was acquired using a Sanying Precision Engineering nanoVoxel-3000H microfocus X-ray CT machine. The X-ray tube voltage and current were set to 160kV and 50 µA during CT scanning. A 1mm thick Cu filter was mounted on the X-ray tube to reduce the beam-hardening effect. A total of 1440 projection images were collected when the specimen was rotated for 360°. A Varian detector with a native pixel size of 127 μm was used to capture the X-ray projection images. The sample to detector distance (SDD) was 635.88 cm and the exposure time for each projection image was 2 seconds. The effective pixel size of the projection image was 2.996 μm. Ten flatfield images were collected before scanning, which were used for background reduction for all projection images to reduce the influence of background noise for CT reconstruction. Using the native reconstruction software for the Nanovox EL-3000H X-ray 3D high-resolution imaging system, a total of 1536 CT slices were reconstructed with an iterative reconstruction method. The CT slices have been analyzed using the DCM software (http://research.csiro.au/dcm). The CT slices were analyzed using the DCM nonlinear optimization module. The DCM software default values were used for all parameters.&rft.creator=Yang, Sam &rft.creator=Wang, Haipeng &rft.creator=Wang, Jinxiu &rft.creator=Wang, Runhua &rft.creator=Li, Jianli &rft.creator=Liu, Rui &rft.date=2022&rft.edition=v1&rft_rights=All Rights (including copyright) CSIRO, Shanxi University 2022.&rft_rights=Creative Commons Attribution-No Derivatives Licence https://creativecommons.org/licenses/by-nd/4.0/&rft_subject=Stainless steel 316L, microstructure, X-ray CT, data-constrained modelling, DCM&rft_subject=Metals and Alloy Materials&rft_subject=ENGINEERING&rft_subject=MATERIALS ENGINEERING&rft_subject=Surfaces and Structural Properties of Condensed Matter&rft_subject=PHYSICAL SCIENCES&rft_subject=CONDENSED MATTER PHYSICS&rft.type=dataset&rft.language=English Access the data

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All Rights (including copyright) CSIRO, Shanxi University 2022.

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Brief description

The sample used in this study was a commercial 316Lstainless-steel bar. The X-ray CT specimen was machined to a cylindrical shape with a length of 1cm and diameter of 2mm. The sample surface was polished by hand with a sandpaper. The X-ray projection images of the specimen was acquired using a Sanying Precision Engineering nanoVoxel-3000H microfocus X-ray CT machine. The CT slices have been analyzed using the DCM software.

Lineage

The X-ray projection images of the specimen was acquired using a Sanying Precision Engineering nanoVoxel-3000H microfocus X-ray CT machine. The X-ray tube voltage and current were set to 160kV and 50 µA during CT scanning. A 1mm thick Cu filter was mounted on the X-ray tube to reduce the beam-hardening effect. A total of 1440 projection images were collected when the specimen was rotated for 360°. A Varian detector with a native pixel size of 127 μm was used to capture the X-ray projection images. The sample to detector distance (SDD) was 635.88 cm and the exposure time for each projection image was 2 seconds. The effective pixel size of the projection image was 2.996 μm. Ten flatfield images were collected before scanning, which were used for background reduction for all projection images to reduce the influence of background noise for CT reconstruction. Using the native reconstruction software for the Nanovox EL-3000H X-ray 3D high-resolution imaging system, a total of 1536 CT slices were reconstructed with an iterative reconstruction method. The CT slices have been analyzed using the DCM software (http://research.csiro.au/dcm). The CT slices were analyzed using the DCM nonlinear optimization module. The DCM software default values were used for all parameters.

Data time period: 2021-12-23

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