Richard E. Martin

Cleveland State University, Cleveland, Ohio

Donald J. Roth and Jonathan A. Salem

Glenn Research Center, Cleveland, Ohio

Application of Advanced Nondestructive Evaluation 

Techniques for Cylindrical Composite Test Samples

NASA/TM—2013-216612

December 2013
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Richard E. Martin

Cleveland State University, Cleveland, Ohio

Donald J. Roth and Jonathan A. Salem

Glenn Research Center, Cleveland, Ohio

Application of Advanced Nondestructive Evaluation 

Techniques for Cylindrical Composite Test Samples

NASA/TM—2013-216612

December 2013

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135
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Level of Review: This material has been technically reviewed by technical management. 
NASA/TM—2013-216612 1 

Application of Advanced Nondestructive Evaluation Techniques for 

Cylindrical Composite Test Samples 

Richard E. Martin 

Cleveland State University 

Cleveland, Ohio 44115 

Donald J. Roth and Jonathan A. Salem 

National Aeronautics and Space Administration 

Glenn Research Center 

Cleveland, Ohio 44135 

Abstract 

Two nondestructive methods were applied to composite cylinder samples pressurized to failure in 

order to determine manufacturing quality and monitor damage progression under load. A unique 

computed tomography (CT) image processing methodology developed at NASA Glenn Research Center 

was used to assess the condition of the as-received samples while acoustic emission (AE) monitoring was 

used to identify both the extent and location of damage within the samples up to failure. Results show the 

effectiveness of both of these methods in identifying potentially critical fabrication issues and their 

resulting impact on performance. 

Introduction 

Composite materials are widely used in many high-performance structures. The successful 

replacement of traditional materials with composites is due to their high specific strength and stiffness 

coupled with cost effectiveness. Although these materials are attractive because of the properties 

mentioned, there is still a need to better understand potential issues regarding manufacturing-related 

defects and their effects on mechanical properties (Refs. 1 and 2). In particular, improper fiber alignment, 

porosity and delaminations may impact response to design loads and should be identified prior to placing 

a component in service. To address these issues, a number of nondestructive evaluation tools have been 

applied to composites to identify performance and life limiting defects with varying degrees of success 

(Ref. 3). Inspection of composites is more difficult than examination of traditional metallic components 

because of the non-uniform material architecture. Inspection is even more challenging when complex 

shapes must be examined. This study seeks to identify and apply advanced NDE techniques that can be 

used as tools for material development and eventually applied to component testing. In particular two 

NDE methods, advanced computed tomography (CT) and acoustic emission (AE), were applied to 

cylindrical composite samples to identify manufacturing-related defects and track both damage 

progression and location as the samples were loaded to failure. This coupled approach is used to help 

determine if material defects found prior to testing have a significant impact on the response of the 

material under load. The following sections describe the samples used, the methods employed, and the 

experimental findings. 
NASA/TM—2013-216612 2 

Experimental Setup 

Test Samples 

Three 6 in. (152.4 mm) long carbon-epoxy composite tube samples were used in this experiment. A 

representative sample is shown in Figure 1. Samples were fabricated using a preform of overbraided 

layers of triaxial braid carbon fiber with the axial tows of the braid running in the axial direction of the 

tube. The finished composite was formed by resin transfer molding using a 3502 epoxy resin. Final 

dimensions were an inner diameter of 4 in. (102 mm) and a wall thickness of 0.140 in. (3.6 mm). Visual 

examination of the samples indicated discontinuities on the outer surface of the cylinder at the locations 

where the outer mold sections joined together as well as some visible fiber misalignment on the sample 

exterior surfaces. 

Mechanical Testing 

Tube samples were loaded to failure using a pressurized tube test method, shown schematically in 

Figure 2, which produces a good approximation of pure transverse tension in the central region where 

failure initiates. This method yields strength values comparable to axial strength values, which is what 

would be expected because of the balance fiber architecture. Loading of the pressurized plug in the tube 

was accomplished by using a servo-hydraulic load frame in stroke control to provide the necessary 

compressive load. Along with load information, strain data was collected using a digital image correlation 

(DIC) system with a surface speckle pattern that is given 3D coordinates which are tracked from one 

image to another. From the calculated 3D deformations, a wide array of deformation based measurements 

can be calculated. The speckle pattern consists of random high contrast black and white speckles applied 

with aerosol paint. 

Figure 1.—Representative cylindrical 

composite test sample. 

Figure 2.—Schematic of mechanical test setup. 
NASA/TM—2013-216612 3 

Figure 3.—Microfocus X-ray CT system. 

Computed Tomography (CT) 

Acquisition 

Prior to mechanical testing, the samples were examined using the commercially available Microfocus 

X-ray Computed Tomography (CT) system shown in Figure 3. The system uses a microfocus x-ray cone 

beam source and a fine pitch flat panel digital detector to capture multiple full-field projections at discrete 

rotational increments. Following acquisition, the projection data was software reconstructed using the 

Feldkamp filtered backprojection technique (Ref. 4) to provide a series of cross-sectional slices that can 

be rendered as a volume. Specifically, the system employed for this testing utilized an X-ray WorX 

XWT-225-THE microfocus X-ray 225 kV source coupled with a Dexela 2923 Detector (0.0748 mm 

pitch, 2923 cm area, and 38883072 pixel elements). Data acquisition, motion control and 

reconstruction were accomplished using software from NSI, Inc. 

Data Analysis 

Traditionally, 3-D CT data visualization is performed by examining orthogonal slices from 

volumetric data. Depending on the geometry of the part, these views can be limiting in terms of providing 

useful information regarding flaws. In the case of the composite tubes used in this study, cross-sections 

tend to only provide thin strips of data corresponding to the thickness of the sample and offer little 

information regarding fiber orientation, ply layup or flaw morphology (Fig. 4). In many instances large 

flaws can be completely overlooked due to their relatively small size against the background in the crosssectional view. Also, due to the high pixel resolution of the detector used, resulting CT reconstructions 

tend to be very large. In the case of this study, data sets with over 2700 cross-sectional images and a total 

size of nearly 14 Gb were generated. Paging through such a large number of high resolution images tends 

to be impractical for an inspector. As an alternative, volume renderings of the data can offer some insight 

regarding the condition of the part (Fig. 5), but results tend to be sensitive to the settings used to generate 

the volume rendering (i.e., contrast, transparency) and can also lead to missed flaws. 

In the case of cylindrical samples, is has been shown to be beneficial to examine the volumetric CT 

data as a series of circumferential slices rather than traditional orthogonal projections (Ref. 5). Using this 

technique, 2-D “sheets” of data can be visualized from interior to exterior rather than simply looking at 

thin cross-sections. As an added benefit, for relatively thin cylindrical samples, the resulting number of 

images is significantly reduced when compared to the original data set. In order to accomplish this unique 

visualization approach, NASA GRC has developed a dedicated cylindrical CT data unwrapper/reslicer 

software program (CT-CURS) (Ref. 5). The program automatically performs all of the necessary preprocessing functions such as histogram matching and slice alignment necessary to accurately reconstruct 

the resliced data. Using the known voxel resolution of the acquired data set, the software enables the user 

to accurately measure features of interest in either the resliced view or traditional cross-sectional view. 

Additional features are also available to perform advanced image processing and feature identification on the 

data sets. CT-CURS is available for download by U.S. citizens at https://sr.grc.nasa.gov/public/project/86/. 

X-ray Source

Sample 

Detector
NASA/TM—2013-216612 4 

Figure 4.—Typical orthogonal projection results for composite tube sample. 

Enlarged view of horizontal cross-section shown in bottom right. 

Figure 5.—Typical volume rendering result 

for composite tube sample. 
NASA/TM—2013-216612 5 

Figure 6.—CT experimental setup. Figure 7.—Acoustic emission sensor placement.

CT Test Setup 

Composite tube samples were placed between the x-ray source and detector in a position to provide 

maximum magnification while keeping the gage section of the sample within the detector field of view 

(Fig. 6). A source-to-object distance of 540 mm and a source to detector distance of 800 mm resulted in a 

magnification factor of approximately 1.5. X-ray source power used was 15 W (75 kV, 200 A) with a 

0.254 mm copper filter in front of the source. Projection images were captured every 0.2 (1800 views) 

with a 4 frame average at each position. The voxel size of the reconstructed data sets was approximately 

50 m. Thin clay markers were placed on the surface of the sample to locate both the zero position of the 

part and the mark the gage length of the burst test area. 

Acoustic Emissions 

Acquisition 

Acoustic emission data was collected during the test using a commercially available four channel 

acoustic emission system from Digital Wave Corporation. Four broadband (100 kHz-3 MHz) sensors 

were coupled to the sample using vacuum grease at 90 increments and alternating from top to bottom as 

shown in Figure 7 in order to cover the entire sample area. Waveform data for each AE event was 

collected at 5 MHz and stored for later processing. Events detected by a single sensor during loading 

triggers data acquisition on all sensor channels simultaneously, enabling location calculations to be 

performed based on AE arrival times. Load data from the test rig was collected along with the AE event 

data for later correlation. Prior to testing, a series of lead break tests were performed to determine wave 

speeds used for location calculations. 

Data Processing 

Acquired signals were post-processed using the AE system software. Processing steps included 

automated and manual filtering of the data to eliminate low energy noise events and events occurring after 

sample failure. Cylindrical location of the AE events based on arrival times and experimentally 

determined wave speeds was then performed and saved along with load data. For better visualization of 

the results, spreadsheet macros were written to post-process the AE and load data, and to present the 

results in a more useable format for analysis. 

Source Object

Detector
NASA/TM—2013-216612 6 

Results 

Mechanical Testing Results 

Mechanical response for the three composite tube samples is shown in Figure 8 with a photo of a 

failed sample shown in Figure 9. Strain response data in the transverse direction indicates a nearly linear 

response to failure with failure strains in the range of 1.7 to 1.9 percent based on DIC data. One of the 

samples, 1038B, did show a stiffer response and a higher failure load than the other samples. Full field 

DIC results near failure show non-uniformity in the strain field. An example of this behavior is shown in 

Figure 10.

Figure 8.—Load-strain response for samples tested to failure. 

Figure 9.—Photograph of failed 

sample 1038A. 

Figure 10.—Full field transverse strain response for 

sample 1038A near failure. 

50

45

40

35

30

25

20

15

10

5

0

0 0.005 0.01 0.015 0.02

Load(kips)

TransverseStrain(in/in)

Loadvs.TransverseStrain

1038A 1038B 1044
NASA/TM—2013-216612 7 

AE Results 

A summary of the cumulative acoustic emission response for the three samples is shown in Figure 11. 

All three of the samples exhibited a similar response with an initiation of AE activity around 4,000 lb 

followed by a nearly linear increase of activity starting at 10,000 lb and continuing until failure much like 

the load-strain response shown previously. As expected, the sample with the higher failure load, 1038B, 

resulted in a higher amount of total AE activity. 

Results from post-processing of the AE data in terms of location are shown in Figures 12 to 14. 

Location of the individual events in both the axial and circumferential directions over the load history 

were calculated and plotted. All of the samples appear to show the same trends in terms of location. In the 

axial direction, AE activity initially begins in a narrow region within the gage region of the sample. As 

the load increases, the distribution of AE activity begins to widen and extend slightly beyond the edges of 

the gage region where it remains until reaching failure load. All three samples also contained a small 

amount of activity near the ends of the sample which is most likely due to noise from the load frame and 

fixturing. 

AE event activity in the circumferential direction also displays a noticeable trend. During the loading 

history of each of the samples, there is a background level of AE activity detected over the entire 

circumference of the sample starting at the initiation load. Coupled with this background activity, there 

are one or two locations on each sample where AE events are concentrated. These peaks begin to form at 

the earliest stages of activity and continue until failure. In all three cases, the location with the highest 

peaks can be associated with the eventual failure location suggesting that the location of damage leading 

to failure occurs early in the loading process. Other significant peaks in the data correlate well with the 

locations of the mold lines of the cylinder. 

Figure 11.—Cumulative acoustic emission activity as a function of load. 

0

5000

10000

15000

20000

25000

0 10000 20000 30000 40000 50000

CumulativeAEEvents

Load(lb.)

AEEventsvs.Load

1038A 1038B 1044
NASA/TM—2013-216612 8 

Figure 12.—Axial and circumferential location data for sample 1038A. 

Figure 13.—Axial and circumferential location data for sample 1038B. 

Figure 14.—Axial and circumferential location data for sample 1044. 

 
NASA/TM—2013-216612 9 

CT Results 

Figures 15 to 17 show the CT results following the unwrap/reslice procedure. For each of the 

samples, two circumferential locations are shown. The red circle in the small cross-sectional view 

indicates the radial depth of the resliced image. A location near the surface is shown to highlight 

variations at the mold lines due to manufacturing. A second circumferential slice is shown at a location 

below the surface to demonstrate the ability of the reslice technique to highlight material architecture, 

locate variations related to manufacturing and identify subsurface defects. Along with each of the images, 

a marker identifying the failure location is provided. 

In the case of the first sample, 1038A, failure occurred near the mold line opposite the zero markers 

on the sample. Discontinuities on the outer surface are clearly visible in the resliced image near the outer 

surface and by visually examining the sample. Below the surface the fiber architecture appears to be 

uniform with no significant indications of manufacturing related flaws such as porosity. In contrast, 

sample 1038B shows a significant amount of non-uniformity in the fiber layout both at the surface and 

throughout the thickness of the sample. Issues such as waviness in both the axial and bias tows can be 

clearly seen distributed around the entire sample circumference and concentrated mainly in the top half of 

the sample coupled with the mold line discontinuities previously observed. No significant indications of 

porosity or resin rich regions below the surface were identified in any of the resliced images. Failure of 

the sample appears to have initiated between two mold lines as identified in Figure 16. CT results did not 

identify any specific indication at this location that may point to the root cause of failure. It is interesting 

to note that this specimen had the highest failure load of the tested samples, implying that mold lines are 

critical to strength. The final sample, 1044, demonstrated a mold line failure similar to 1038A. Examination of the resliced CT results indicates similar discontinuities associated with the mold line but also 

shows a line of porosity visible at the sample surface as a long dark line in the axial direction. Below the 

surface, the same area contains more distributed porosity that appears to follow the bias tow direction and 

is concentrated at the top of the sample and near the failure location. 

Figure 15.—Sample 1038A CT reslice results. 
NASA/TM—2013-216612 10 

Figure 16.—Sample 1038B CT reslices results. Not nonuniformity at exterior surface and 

interior positions. 

Figure 17.—Sample 1044 CT results. Porosity line shown circled in green. 
NASA/TM—2013-216612 11 

Conclusions 

Data collected for a series of cylindrical composite tube samples using a high resolution CT system 

and using advanced image processing tools was analyzed to assess the material in the as received 

condition and identify potential defects that may affect load capacity. Results of this study demonstrate 

the ability of the technique to identify manufacturing related issues such as fiber misalignment and 

subsurface porosity as well as near-surface defects related to the molding process. This type of 

information can be used to not only improve fabrication methods, but may also identify anomalies that 

can lead to early failure. In the case of the samples used in this study, mold line discontinuities appear to 

dominate failure in two out of the three samples with the addition of subsurface porosity as a possible 

contributor. Issues such as fiber misalignment did not appear to have a significant effect on ultimate 

strength. In fact, the sample that appeared to have the most non-uniformity in terms of architecture also 

had the highest failure load. 

As a monitoring tool, acoustic emission testing was shown to be an effective way to assess the 

behavior of the composite samples under load. Information regarding damage initiation loads and damage 

accumulation rates can be determined from examination of the AE data over the loading history and can 

be used as a comparison tool in future material development. Processing of the AE data to isolate event 

locations offers a more detailed picture of damage progression within the material. Coupled with the 

information gathered by other nondestructive methods such as CT and visual examination, specific issues 

leading to failure can be identified and used to suggest areas for improvement in both material and 

component development. 

References 

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polymer composite materials,” Review of Progress in Quantitative Nondestructive Evaluation. 

Volume 31, 17–22 July 2011, Burlington, VT, pp. 1080–1087. 

2. Hsiao H.M., Daniel I.M., “Elastic properties of composites with fiber waviness,” Composites Part A: 

Applied Science and Manufacturing, Volume 27, Issue 10, 1996, Pages 931–941. 

3. Vaara, Pauli, and Jukka Leinonen. “Technology Survey on NDT of Carbon-fiber Composites,” 

(2012). 

4. Feldkamp, L.A., Davis, L.C., and Kress, J.W., “Practical cone-beam algorithm,” J. Opt. Soc. Amer. 

A6 (1984), 612–619. 

5. Roth, D.J., Burke, E.R., Rauser, R.W., and Martin, R.E., “A Novel Automated Method for Analyzing 

Cylindrical Computed Tomography Data,” Extended Abstract Paper Proceedings at Fall 2011 ASNT 

conference. Palm Springs Convention Center, Palm Springs, California. October 24–28. pp. 139–145.