This work reports three reconstruction algorithms developed to address the practical issues encountered in 3D tomography diagnostics, such as the limited view angles available in many practical applications, the large scale and nonlinearity of the problems when they are in 3D, and the measurement uncertainty. These algorithms are: an algebraic reconstruction technique (ART) screening algorithm, a nonlinear iterative reconstruction technique (NIRT), and an iterative reconstruction technique integrating view registration optimization (IRT-VRO) algorithm. The ART screening algorithm was developed to enhance the performance of the traditional ART algorithm to solve linear tomography problems, the NIRT was to solve nonlinear tomography problems, and the IRT-VRO was to address the issue of view registration uncertainty in both linear and nonlinear problems. This dissertation describes the mathematical formulations, and the experimental and numerical validations for these algorithms. It is expected that the results obtained in this dissertation to lay the groundwork for their further development and expanded adaption in the deployment of tomography diagnostics in various practical applications. / Ph. D. / Tomography is a technique to obtain three-dimensional (3D) measurements noninvasively, and such nonintrusive nature has made it a powerful and indispensable tool for a wide variety of applications. Regardless of the specific implementation and application of tomography techniques, they generally involve two steps. In the first step, 2D projections of the target object are captured from different orientations; and in the second step, the 2D projections obtained in step 1 are fed into a reconstruction algorithm to obtain the 3D measurements.
This dissertation focuses on the second step, more specifically, the development and validation of reconstruction algorithms under the context of flow and flame imaging. Existing reconstruction algorithms encountered various limitations when applied to turbulent flow and flames due to various factors, such as the limited number of projections available, scale of the problem, and nonlinear effects. This work reports three reconstruction algorithms developed to overcome some of these practical issues: an algebraic reconstruction technique (ART) screening algorithm, a nonlinear iterative reconstruction technique (NIRT), and an iterative reconstruction technique integrating view registration optimization (IRT-VRO) algorithm. These new algorithms were demonstrated to enhance the spatial resolution, computational efficiency, accuracy, and to address nonlinear effects of tomographic measurements.
This work describes the mathematical formulations, and the experimental and numerical validations of these algorithms. It is expected that the results obtained in this work to lay the groundwork for their further development and expanded adaption in the deployment of tomography diagnostics in various practical applications.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/74233 |
| Date | 10 January 2017 |
| Creators | Lei, Qingchun |
| Contributors | Mechanical Engineering, Ma, Lin, Huxtable, Scott T., Lowe, K. Todd, Liu, Yang, Xiao, Heng |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.002 seconds