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Research Papers: Gas Turbines: Ceramics

Multi-Lead Direct Current Potential Drop Method for In Situ Health Monitoring of Ceramic Matrix Composites

[+] Author and Article Information
Yogesh P. Singh

Department of Mechanical Engineering,
University of Akron,
ASEC 504,
Akron, OH 44325
e-mail: ysingh@uakron.edu

Michael J. Presby

Department of Mechanical Engineering,
University of Akron,
ASEC 504,
Akron, OH 44325
e-mail: mjp80@zips.uakron.edu

Manigandan Kannan

Department of Mechanical Engineering,
University of Akron,
ASEC 504,
Akron, OH 44325
e-mail: mk77@uakron.edu

Gregory N. Morscher

Department of Mechanical Engineering,
University of Akron,
ASEC 504,
Akron, OH 44325
e-mail: gm33@uakron.edu

1Corresponding author.

Contributed by the Ceramics Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received July 30, 2018; final manuscript received August 5, 2018; published online October 4, 2018. Editor: Jerzy T. Sawicki.

J. Eng. Gas Turbines Power 141(3), 031301 (Oct 04, 2018) (10 pages) Paper No: GTP-18-1532; doi: 10.1115/1.4041271 History: Received July 30, 2018; Revised August 05, 2018

The method of direct current potential drop (DCPD) can be utilized as an effective and convenient approach for in situ damage detection, and as a nondestructive evaluation technique. We present the results from use of a multiprobe DCPD technique for in situ damage detection in loading of a SiC/SiC composite. It is shown that in three different modes of loading (monotonic, fatigue, and cyclic load–unload), the sensing capabilities of DCPD technique compare well to the techniques of modal acoustic emission (AE) and digital image correlation (DIC). It was also found that DCPD technique provides a far earlier warning of failure under fatigue loading than the other two methods. In addition, we show that strategically placed multiple voltage leads on the specimen surface provide a promising way of qualitatively determining the crack initiation site. Therefore, the use of multiple lead DCPD method, together with other techniques, provides a viable option for sensing damage in ceramic matrix composites (CMCs) with complex geometries, and for applications at higher temperatures.

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References

Mansour, R. , Singh, Y. P. , Kannan, M. , Morscher, G. N. , Abdi, F. , Ahmad, J. , Godines, C. , DorMohammadi, S. , and Choi, S. , 2017, “ Study of Interlaminar Fracture Properties of Ceramic Matrix Composites at Room and Elevated Temperatures,” ASME Paper No. GT2017-65168.
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Figures

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Fig. 1

(a) Photograph of a dog-boned specimen with a notch cut in the middle of one edge, painted area for DIC imaging, and the locations of 6 point contacts on top surface for DCPD measurement. Other 6 point contacts were placed on back surface of specimen at symmetrically opposite locations to the top point contacts. (b) A schematic of the specimen showing the locations of different probes, and current leads.

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Fig. 2

Change in ER as a function of notch length for different lead pair combinations. The lead pairs from notch side show clear increase in ER with increasing crack length, while pairs from far side are almost insensitive to crack length.

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Fig. 3

Measured direct current potential drops as a function of time. The data is for different pairs of leads from the top and the bottom surfaces of the specimen, and for testing via three different modes of loading: (a) monotonic tensile load, (b) loading in fatigue mode, and (c) cyclic load–unload.

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Fig. 4

Results from monotonic tensile loading experiment. (a) Applied Load and measured potential drop on left vertical axis, maximum cumulative AE energy, and crack length on right vertical axis. (b) Strain intensity distribution of top surface with corresponding optical images from DIC. The visible crack in the optical images is outlined in red for clarity. Note: Due to the speckle pattern, it is difficult to determine the precise location of the crack tip from the optical images.

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Fig. 5

Digital image correlation crack length analysis: (a) optical image, (b) DIC surface strain map, and (c) schematic of correlation windows used to determine COD

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Fig. 6

Results from loading in fatigue mode: (a) measured potential drop on left vertical axis, maximum cumulative AE energy, and crack length on right vertical axis, (b) step fatigue loading, and (c) strain intensity distribution and optical images from DIC of the top surface

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Fig. 7

Results from cyclic load–unload test:(a) Measured potential drop on left vertical axis; load, maximum cumulative AE energy, and crack length on right vertical axis, (b) graph (a) zoomed in for a small time interval for better resolution

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Fig. 8

Comparing strain intensity distribution from DIC with potential drops across different lead pairs in cyclic load–unload test

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Fig. 9

(a) Direct current potential drop derivative for different lead pairs highlighting areas of interest where damage is occurring, and DIC images from the (b) top and (c) bottom surfaces of the specimen. Top picture shows lead locations on the top surface of the specimen. Lines connecting the leads represent the examples of length across which the potential difference is measured. Solid lines represent the path on the surface while the dotted lines are path going in the bulk. Bottom picture is the image of top surface of specimen after failure.

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Fig. 10

Direct current potential drop derivatives for different pairs of leads in cyclic load–unload test. The duration of test is broken into smaller time intervals for the sake of clarity, and graphs from (a)–(f) show the data in successive time intervals from the beginning to the end of the test.

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Fig. 11

Strain intensity distribution on the top surface of the specimen, obtained using DIC images recorded during cyclic load–unload test. Also shown are the load data to show the correspondence between the damage and the peak load of a cycle.

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