Hostname: page-component-89b8bd64d-9prln Total loading time: 0 Render date: 2026-05-07T11:46:09.769Z Has data issue: false hasContentIssue false

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

Published online by Cambridge University Press:  14 May 2019

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
Get access

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.

Information

Type
Technical Article
Copyright
Copyright © International Centre for Diffraction Data 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable