scholarly journals X-ray Computed Tomography Data ofAdditive Manufacturing Metrology Testbed (AMMT) Parts: “Overhang Part X4”

2020 ◽  
Vol 125 ◽  
Author(s):  
Max Praniewicz ◽  
Brandon Lane ◽  
Felix Kim ◽  
Christopher Saldana
Keyword(s):  
Additive Manufacturing ◽  
Three Dimensional ◽  
Sensor Data ◽  
X Ray ◽  
Surface Data ◽  
Design Build ◽  
X Ray Computed ◽  
In Situ Sensor ◽  
Stereolithography Files

This document provides details on the data and files generated from post-build X-ray computedtomography (XCT) measurements of the four parts built as part of the “Overhang Part X4” dataset. The “Overhang Part X4” dataset was a three-dimensional (3D) additive manufacturing (AM) build performed on the Additive Manufacturing Metrology Testbed (AMMT) by Ho Yeung and Brandon Lane on June 28, 2019. The files discussed in this document include image sequences for each part, stereolithography files (.STL) of the surface data extracted from XCT. This data is one of a set of “AMMT Process Monitoring Datasets”, as part of the Metrology for Real-Time Monitoring of Additive Manufacturing project at the National Institute of Standards and Technology (NIST). In-situ sensor data, part design, build command and scan strategy data, materials, and associated metadata for this build are described in Ref. [1]. Readers should refer to the AMMT datasets web page for updates.

scholarly journals Process Monitoring Dataset from the Additive Manufacturing Metrology Testbed (AMMT): Overhang Part X4

2020 ◽  
Vol 125 ◽  
Author(s):  
Brandon Lane ◽  
Ho Yeung
Keyword(s):  
Computed Tomography ◽  
Additive Manufacturing ◽  
Real Time ◽  
Process Monitoring ◽  
Three Dimensional ◽  
Ex Situ ◽  
Web Page ◽  
X Ray ◽  
X Ray Computed

This document provides details on the files available in the dataset “Overhang Part X4” pertaining to a three-dimensional (3D) additive manufacturing (AM) build performed on the Additive Manufacturing Metrology Testbed (AMMT) by Ho Yeung and Brandon Lane on June 28, 2019. The files include the input command files, materials data, in-situ process monitoring data, and metadata. This data is one of a set of “AMMT Process Monitoring Datasets”, as part of the Metrology for Real-Time Monitoring of Additive Manufacturing project at the National Institute of Standards and Technology (NIST). Ex-situ part characterization data, including X-ray computed tomography (XCT) measurements, will be provided as it is made available. Readers should refer to the AMMT datasets web page for updates.

Responsive alignment for X-ray tomography beamlines

2018 ◽  
Vol 25 (6) ◽  
pp. 1774-1779
Author(s):  
Gustavo José Querino de Vasconcelos ◽  
Eduardo Xavier Miqueles ◽  
Gabriel Schubert Ruiz Costa
Keyword(s):  
Rotation Axis ◽  
Three Dimensional ◽  
Image Features ◽  
Ct Reconstruction ◽  
Reconstruction Algorithms ◽  
Parallel Beam ◽  
X Ray ◽  
Three Dimensional Representation ◽  
X Ray Computed

X-ray computed tomography (CT) is an imaging technique intended to obtain the internal structure and three-dimensional representation of a sample. In general, parallel-beam CT reconstruction algorithms require a precise angular alignment and knowledge of the exact axis of rotation position. Highly brilliant X-ray sources with ever-increasing data-acquisition rates demand optimized alignment techniques to avoid compromising in situ data analysis. This paper presents a method to automatically align the angular orientation and linear position of the rotation axis in a tomography setup, correlating image features from different X-ray projections.

In Situ Visualization and Quantification of Three-Dimensional Root System Architecture and Growth Using X-Ray Computed Tomography

2014 ◽  
Vol 13 (8) ◽  
pp. vzj2014.03.0024 ◽  
Author(s):  
Nicolai Koebernick ◽  
Ulrich Weller ◽  
Katrin Huber ◽  
Steffen Schlüter ◽  
Hans-Jörg Vogel ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Root System ◽  
System Architecture ◽  
Three Dimensional ◽  
Root System Architecture ◽  
X Ray ◽  
In Situ Visualization ◽  
X Ray Computed

Three dimensional imaging of plant roots in situ with X-ray Computed Tomography

1997 ◽  
Vol 189 (2) ◽  
pp. 167-179 ◽  
Author(s):  
D.A. Heeraman ◽  
J.W. Hopmans ◽  
V. Clausnitzer
Keyword(s):  
Computed Tomography ◽  
Three Dimensional ◽  
Plant Roots ◽  
Three Dimensional Imaging ◽  
X Ray ◽  
X Ray Computed

scholarly journals Three-dimensional Analysis of an In Situ Double-torsion Test by X-ray Computed Tomography and Digital Volume Correlation

2013 ◽  
Vol 53 (7) ◽  
pp. 1265-1275 ◽  
Author(s):  
P. Leplay ◽  
J. Réthoré ◽  
S. Meille ◽  
M.-C. Baietto ◽  
J. Adrien ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Dimensional Analysis ◽  
Three Dimensional ◽  
Torsion Test ◽  
Digital Volume Correlation ◽  
X Ray ◽  
X Ray Computed ◽  
Double Torsion

scholarly journals Three‐dimensional X‐ray‐computed tomography of 3300‐ to 6000‐year‐old Citrullus seeds from Libya and Egypt compared to extant seeds throws doubts on species assignments

2021 ◽  
Author(s):  
Katherine A. Wolcott ◽  
Guillaume Chomicki ◽  
Yannick M. Staedler ◽  
Krystyna Wasylikowa ◽  
Mark Nesbitt ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Three Dimensional ◽  
X Ray ◽  
X Ray Computed

Visualizing Fluid Flows With X-Rays

2007 ◽  
Author(s):  
Theodore J. Heindel ◽  
Terrence C. Jensen ◽  
Joseph N. Gray
Keyword(s):  
Computed Tomography ◽  
Flow Visualization ◽  
Three Dimensional ◽  
Fluid Flows ◽  
X Rays ◽  
Radiographic Images ◽  
Optical Access ◽  
X Ray ◽  
X Ray Computed ◽  
Density Map

There are several methods available to visualize fluid flows when one has optical access. However, when optical access is limited to near the boundaries or not available at all, alternative visualization methods are required. This paper will describe flow visualization using an X-ray system that is capable of digital X-ray radiography, digital X-ray stereography, and digital X-ray computed tomography (CT). The unique X-ray flow visualization facility will be briefly described, and then flow visualization of various systems will be shown. Radiographs provide a two-dimensional density map of a three dimensional process or object. Radiographic images of various multiphase flows will be presented. When two X-ray sources and detectors simultaneously acquire images of the same process or object from different orientations, stereographic imaging can be completed; this type of imaging will be demonstrated by trickling water through packed columns and by absorbing water in a porous medium. Finally, local time-averaged phase distributions can be determined from X-ray computed tomography (CT) imaging, and this will be shown by comparing CT images from two different gas-liquid sparged columns.

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