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3D immersive visualization of micro-computed tomography and XRD texture datasets

Published online by Cambridge University Press:  14 May 2019

M. A. Rodriguez ,
T. T. Amon ,
J. J. M. Griego ,
H. Brown-Shaklee  and
N. Green
M. A. Rodriguez*
Affiliation:
Sandia National Laboratories, Albuquerque, New Mexico 87185-1411
T. T. Amon
Affiliation:
Sandia National Laboratories, Albuquerque, New Mexico 87185-1411
J. J. M. Griego
Affiliation:
Sandia National Laboratories, Albuquerque, New Mexico 87185-1411
H. Brown-Shaklee
Affiliation:
Sandia National Laboratories, Albuquerque, New Mexico 87185-1411
N. Green
Affiliation:
Department of Energy's Kansas City National Security Campus managed by Honeywell, Kansas City, Missouri 64147
*
a)Author to whom correspondence should be addressed. Electronic mail: marodri@sandia.gov
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Abstract

Advancements in computer technology have enabled three-dimensional (3D) reconstruction, data-stitching, and manipulation of 3D data obtained on X-ray imaging systems such as micro-computed tomography (μ-CT). Likewise, intuitive evaluation of these 3D datasets can be enhanced by recent advances in virtual reality (VR) hardware and software. Additionally, the generation, viewing, and manipulation of 3D X-ray diffraction datasets, such as pole figures employed for texture analysis, can also benefit from these advanced visualization techniques. We present newly-developed protocols for porting 3D data (as TIFF-stacks) into a Unity gaming software platform so that data may be toured, manipulated, and evaluated within a more-intuitive VR environment through the use of game-like controls and 3D headsets. We demonstrate this capability by rendering μ-CT data of a polymer dogbone test bar at various stages of in situ mechanical strain. An additional experiment is presented showing 3D XRD data collected on an aluminum test block with vias. These 3D XRD data for texture analysis (χ, ϕ, 2θ dimensions) enables the viewer to visually inspect 3D pole figures and detect the presence or absence of in-plane residual macrostrain. These two examples serve to illustrate the benefits of this new methodology for multidimensional analysis.

Keywords

3D immersive visualizationmicro-computed tomographyXRD texture datasets
Type
Technical Article
Information
Powder Diffraction , Volume 34 , Issue 2 , June 2019 , pp. 97 - 102
Copyright
Copyright © International Centre for Diffraction Data 2019 

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