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Title

Author

Date of Award

8-2016

Document Type

Subsurface Circular (itch) Mac Os Download

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Legacy Department

Civil Engineering

Committee Member

Dr. Amir Poursaee, Committee Chair

Committee Member

Dr. Prasad Rangaraju

Committee Member

Dr. Brandon Ross

Subsurface Circular (itch) Mac Os Operating System

Committee Member

Dr. Taufiquar Khan

Abstract

Electrical impedance tomography (EIT) based non-destructive evaluation showed great potentials in assessing the health condition of the new or existing civil infrastructures. Damages or anomalies that on the surface and embedded inside the structures exhibited as local conductivity changes and altered the path of electrical current flow. This investigation was focused on developing a new automated EIT system and employing EIT to identify the anomalies in cementitious materials structures.

This dissertation is structured as follows. First, common nondestructive evaluation (NDE) techniques including conductivity-based techniques were summarized as well as their advantages and disadvantages. Then the theories of EIT modality as well as inverse reconstruction algorithms were illustrated. Next, the development of the automated electrical tomography measurement system was presented which made it possible to complete thousands of measurements in a few minutes. The developed system has multiple portable measurement units that can be used on the objects with different geometries. Finally, experiments were designed and the results of the experimental works were discussed.

Laboratory experiments were carried out to explore the feasibility of implementing the EIT in assessing surface and subsurface damages in cementitious structures. With the aid of conductive paint, the tests were performed on both circular surfaces and a large polyester transparent sheet. Damages with different geometries and sizes were identified. Furthermore, the feasibility of detecting subsurface (invisible) damages was investigated. With the aid of numerical simulation and inverse calculation, the locations of damages were identified and the sizes were qualitatively estimated. In addition, experiments were designed to assess the chloride distribution in concrete slabs. The results from the EIT tests were compared to results from half-cell potential (HCP) and four-point resistivity tests. The results corresponded very well and EIT reconstructed images showed clearer contrast.

Another application was to detect the distribution of steel fibers in steel reinforced mortar specimens using the EIT. The mortar specimens were cast with two different water to cementitious materials ratios 0.5 and 1.25, respectively. The fiber levels in volume percentages ranging from 0 to 2% with an increment of 0.5%. Comparative study was carried out with the aid of advanced photography techniques and image processing techniques. Results showed a great potential for the EIT method to be used in this application.

To summarize, EIT was proved to be a viable NDE tool for damage detection in cementitious structures. Despite the potentials of EIT in NDE of cementitious materials, challenges exist. First, cementitious materials are heavily heterogeneous with low electrical conductivity. Although conductive paint provided a relatively uniform conductivity field, it was only suitable for accessible surfaces of structures. For subsurface damage detection, the penetration of injected current was not deep enough for accurate damage detection, as a result, only the damages with depths less than 30 mm can be detected. It seems that using more powerful current source could improve the image resolution. Another issue was the ill-posed feature of inverse analysis and more advanced algorithms are needed to enhance the performance and stability of the inverse problems compared to current approaches.

Recommended Citation

Ruan, Tao, 'Development of an Automated Impedance Tomography System and Its Implementation in Cementitious Materials' (2016). All Dissertations. 1756.
https://tigerprints.clemson.edu/all_dissertations/1756

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