Ali Abdul-Aziz and D.J. Roth 

Glenn Research Center, Cleveland, Ohio

R. Cotton

Simpleware Ltd., Exeter, United Kingdom

George F. Studor and Eric Christiansen

Johnson Space Center, Houston, Texas

P.C. Young 

University of Exeter, Exeter, United Kingdom

Material Characterization and Geometric 

Segmentation of a Composite Structure Using 

Microfocus X-Ray Computed Tomography ImageBased Finite Element Modeling 

NASA/TM—2011-217015

July 2011
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Ali Abdul-Aziz and D.J. Roth 

Glenn Research Center, Cleveland, Ohio

R. Cotton

Simpleware Ltd., Exeter, United Kingdom

George F. Studor and Eric Christiansen

Johnson Space Center, Houston, Texas

P.C. Young 

University of Exeter, Exeter, United Kingdom

Material Characterization and Geometric 

Segmentation of a Composite Structure Using 

Microfocus X-Ray Computed Tomography ImageBased Finite Element Modeling 

NASA/TM—2011-217015

July 2011

National Aeronautics and

Space Administration

Glenn Research Center

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NASA/TM—2011-217015 1

Material Characterization and Geometric Segmentation of a

Composite Structure Using Microfocus X-Ray Computed 

Tomography Image-Based Finite Element Modeling 

Ali Abdul-Aziz and D.J. Roth 

National Aeronautics and Space Administration

Glenn Research Center

Cleveland, Ohio 44135

R. Cotton

Simpleware Ltd.

Exeter, United Kingdom

George F. Studor and Eric Christiansen

National Aeronautics and Space Administration

Johnson Space Center

Houston, Texas 77058

P.C. Young1

University of Exeter

Exeter, United Kingdom

Abstract

This study utilizes microfocus x-ray computed tomography (CT) slice sets to model and characterize 

the damage locations and sizes in thermal protection system materials that underwent impact testing.

ScanIP/FE software is used to visualize and process the slice sets, followed by mesh generation on the 

segmented volumetric rendering. Then, the local stress fields around several of the damaged regions are 

calculated for realistic mission profiles that subject the sample to extreme temperature and other severe 

environmental conditions. The resulting stress fields are used to quantify damage severity and make an 

assessment as to whether damage that did not penetrate to the base material can still result in catastrophic 

failure of the structure. It is expected that this study will demonstrate that finite element modeling based 

on an accurate three-dimensional rendered model from a series of CT slices is an essential tool to quantify 

the internal macroscopic defects and damage of a complex system made out of thermal protection 

material. Results obtained showing details of segmented images; three-dimensional volume-rendered 

models, finite element meshes generated, and the resulting thermomechanical stress state due to impact 

loading for the material are presented and discussed. Further, this study is conducted to exhibit certain 

high-caliber capabilities that the nondestructive evaluation (NDE) group at NASA Glenn Research Center 

can offer to assist in assessing the structural durability of such highly specialized materials so 

improvements in their performance and capacities to handle harsh operating conditions can be made.

Introduction

New techniques for generating robust and accurate geometry meshes based on three-dimensional

imaging data have recently been developed, which make the prediction of macrostructural properties 

relatively simple (Ref. 1). The construction accuracy is the focal point in these new techniques along with 

 1

Associate Professor, School of Engineering and Computer Science, University of Exeter, Harrison Building, North 

Park Road, Exeter, EX4 4QF, UK, telephone: +44(0)1392263684, e-mail: philippe.g.young@exeter.ac.uk
NASA/TM—2011-217015 2

the geometric precision, which is highly dependent on the image quality. Algorithms are continuously 

being developed and are used to preserve topology and volume, which in turn facilitate multipart 

geometric modeling. In addition to geometric modeling, different constituent’s materials as separate mesh 

domains can also be identified, and their properties can be assigned based on signal strength in the parent 

image. This will provide a means for modeling continuous variations in properties for an inhomogeneous 

medium. Further, these newer techniques have been embedded into many software codes (e.g., Ref. 2) 

and are being used and applied to analyze various material types including composites.

Additionally, continuous advancements in the field of x-ray computed tomography (CT) have made it 

possible to be used in many other applications besides the medical field. It has made a speedy move into 

the material research area and has become a crucial inspection tool, allowing the measurement of 

volumetric information such as geometric dimensions, voids, and inclusions of complex materials in 

addition to providing pictorial views of the internal and external structure of materials (Ref. 1). One of the 

key features of CT scanning is the ability to use its two-dimensional cross-sectional images to generate an 

accurate three-dimensional visualization and quantification of the internal structure of materials (Refs. 1 

and 2). However, most material CT studies stop after the three-dimensional volumetric rendering of the 

internal structure of the sample. Few material researchers have used CT beyond simple image analysis 

and quantitative image assessment. A few studies extended the use of CT to the generation of highfidelity finite element models from CT slice data to calculate the localized stress and strain field of the 

actual material morphology (Refs. 3 to 9).

Thus, the core of this study is focused on the use of x-ray CT for creating engineering models and 

subsequent simulations using these models to assess durability for a NASA thermal protection system 

(TPS) (Fig. 1). This TPS configuration is under consideration for use in NASA’s multipurpose Orion 

crew module (CM). The TPS utilizes alumina enhanced thermal barrier 128 kg/m3 (8 lb/ft3

) (AETB–8) 

tiles bonded to the CM backshell, which acts as the substrate for the TPS. The substrate is a honeycomb 

panel with a titanium or aluminum honeycomb core bonded to either carbon composite face sheets or 

titanium face sheets. The TPS protects the vehicle and crew from external temperatures during reentry as 

well as impacts from micrometeoroids and orbital debris. The threat of hypervelocity impact from 

micrometeorites, and especially manmade space debris, is an increasing concern for spacecraft. Therefore, 

it is critical to understand how well the TPS can withstand hypervelocity impacts and how well it can 

protect the underlying structure from damage. Microcomputed tomography (micro-CT) image-based 

finite element modeling is used to appraise the structural performance of this material subject to a highvelocity-impact loading. 
NASA/TM—2011-217015 3

A detailed representation showing the material layout of the TPS is shown in Figure 1. The top 

portion including the white coating is the actual proprietary TPS material with a thickness of about 

30 mm including a strain isolation pad (SIP). The SIP is covered from the top and bottom with a roomtemperature vulcanizing (RTV) silicon adhesive and is used as the interfacing layer between the TPS and 

vehicle structure. Note Figure 1 for more details (Refs. 10 and 11).

Different software programs are used to perform various image segmentation and processing 

operations, volume rendering (Ref. 2), and analytical modeling (Ref. 12). This study shows a fusion of 

technologies performed by the NASA Glenn NDE group that is capable of performing and utilizing highresolution x-ray CT data ultimately geared towards engineering studies.

Image Processing and Analytical Approach

The steps and details of the image processing, segmentation, three-dimensional volume rendering,

and mesh generation of the scanned impacted TPS material specimen are illustrated in this section. Finite 

element analyses and the corresponding results are also outlined. Figure 2 shows a side and a top view of 

selected CT slices of the impact-damaged sample. The damaged sample was x-ray CT scanned using a 

Fein-focus FXE 200 keV x-ray source (Fig. 3), and 160 image slices were produced. Each slice was 

converted from raw binary to TIFF format (1200 by 700 pixel resolution). The in-plane resolution of the 

scanner was 0.2 mm (in both x- and y-directions), whereas the separation between each slice was about

0.0376 mm. The voxel dimension on this scan set should be the same (200 μm) in all three directions.

In-house image-processing software (Ref. 1) was used to convert the CT slices into TIFF format to allow 

compatibility with ScanIP/+FE software (Ref. 5).

Data Preparation and Cropping

The images in the two-dimensional set were cropped to remove space not occupied by the sample. 

This resulted in a smaller volume that is close to the actual sample size.
NASA/TM—2011-217015 4

Filtering

Various filtration options are available within the ScanIP software; however, the choice of which 

filter should be applied over others is highly dependent on the nature of the problem, materials, and image 

quality associated with the CT scan. Because of the noisy nature of the image, some filtering was 

necessary. The curvature anisotropic diffusion filter was therefore selected to be used. Note that it is 

considered as a noise reduction filter rather than a smoothing filter because its purpose is to reduce noise 

while preserving features, which is not the case of smoothing filters such as a Gaussian filter. Smoothing 

filters, in contrast to noise filters, will get rid of noise and also smooth or attenuate contours. The

curvature anisotropic diffusion filter was applied here with a conductance of 5, a time step of 0.0625, and 

10 iterations (see users’ manual in Ref. 2).

Figures 4(a) and (b) display a sample CT slice showing prefiltering and postfiltering views. The 

figure simply illustrates the image enhancement due to filtering which helped smoothing.
NASA/TM—2011-217015 5

Image Segmentation

Segmentation is the process of identifying, within an image, what pixels belong to each object of 

interest. In this study, several finite element models were considered, differing by mesh density, 

geometrical definition, or by the way material properties are defined. The segmentation process itself only 

influences the geometrical definition of each model, and there are actually four models that are 

geometrically different. These meshes correspond to individual models of each of the three impact craters 

and a model of the whole sample. An example of the mesh of the full sample with the three impact craters 

can be seen in Figure 5. Figure 5(a) shows a volume rendering of the CT image set, and Figure 5(b)

shows the resulting finite element mesh with transparency visualization. Due to the artifacts in the data 

caused by changes in density of the material, the segmentation process required several steps. The 

artifacts meant that the grayscale values of the matrix varied throughout the three-dimensional volume

model.

Therefore a global threshold would not be suitable; local thresholding on individual or a selection of 

slices was required to ensure the correct geometry of the impact craters was captured. After the local 

thresholding, the paint tool was used to manually enhance and straighten the segmentation. For example, 

regions where the boundary between crater and material was distorted from artifacts were all cleared out 

via the paint and segmentation option available within the software. The process was rather cumbersome,

but it did result in capturing the fine details that represented the core of the materials’ structural 

characteristics. As described, four different masks each representing separate regions were created, with 

the A being the whole matrix and B, C, and C* being the masks representing the individual three craters,

respectively. Figures 6(a) and (b), respectively, show a sector of the segmented material and a 

corresponding transparent view of one of the craters represented by a mask, where features such as the 

honeycomb core, the composite, and the TPS + SIP materials are clearly identified.
NASA/TM—2011-217015 6

Impact Craters Segmentation

The following sequence was applied to segment the crater regions:

A: Pixels of values ranging from 121 to 255 were thresholded to create a part representing the 

matrix.

B: Pixels of values ranging from 121 to 255 were thresholded to create a part representing the 

matrix, and then the holes were floodfilled, with the result of the floodfill being added to the 

mask. The resulting masks consist of a block incorporating both the matrix and the holes.

C: Pixels of values ranging from 121 to 255 were thresholded to create a part representing the 

matrix. Then the holes were floodfilled, a feature within the Simpleware software to help 

optimize the model and invoke a uniform connectivity of surfaces throughout the entire model to 

generate a second part consisting of the holes only (0 to 120).

C*: Same as C, but using different threshold values to define the matrix (125 to 255) and the holes (0

to 124). The grayscale values varied from slice to slice because of the change in contrast from the 

artifacts. Also, the 0 to 255 range is not the original values from the scanner. ScanIP works in 

8-bit grayscale so the higher bit depth data from the scanner is converted to 256 values using a 

windowing-level technique.

Mesh Generation

The ScanFE module (Ref. 2) was further used to generate a number of finite element meshes based on 

the three-dimensional segmented image data. The mesh density generated in ScanFE is closely connected 

to image resolution to explore convergence of results (field parameters of interest); the image was 

downsampled to create several volumes, with each representing a sector of interest to generate high- and 

low-resolution models. As a result, an interesting point can be made here about image-based models 

versus computer-aided design (CAD) models. In CAD models the geometry of the model is assumed to 

be exact, and mesh density is increased principally to obtain a better model of the field parameters of 

interest (i.e., the stress field within a loaded structure). In image-based models, however, both the 

response and the geometry of the system are approximated.
NASA/TM—2011-217015 7

By generating models based on increasing image resolutions, one not only improves the modeling of 

the response, but also the representation of the geometry (one effectively converges to the geometry). 

Hence, one can perform essentially a dual, or coupled, convergence study; however, this type of study 

provides powerful arguments for the validity of the simulations because convergence of results 

demonstrates not only that the mesh is of sufficient density to capture the field parameter of interest, but 

also—and as importantly—that the image resolution on which the model is based is high enough to 

capture relevant features in the scanned object. 

Four models were generated within ScanFE using 40 iterations of Simlpeware’s proprietary multipart 

anti-aliasing (aa) algorithm, followed by two iterations of Laplacian smoothing. The implemented aa 

techniques ensure high accuracy of reconstruction, unlike many smoothing schemes. They preserve

volume, topology, and geometry while ensuring the generation of models whose geometric accuracy is 

contingent only on image quality (i.e., on the accuracy of the segmentation). Mesh optimization

parameters ensured that the element quality index reached a value of 0.15, allowing off-surface nodes 

(within a 10 percent pixel distance).

Figure 7 shows a view of the finite element mesh generated by the ScanFE-Free mesh option. The 

modeling is invoked such that a finer grid is generated around the damaged sites and a coarser mesh

further out. The meshing technique applied takes the initial image-based resolution of the mesh and then 

automatically adapts the mesh around areas of curvature (i.e., craters) and then grows the elements where 

fewer features exist (i.e., the flat boundaries of the part). This will allow more accurate analyses and a 

higher degree of accuracy in capturing stress risers near geometric discontinuities, and it will also help 

reduce the size of the model and the computation time. Figure 8 shows a denser version of the threedimensional rendered volume and the reciprocate finite element model. A notable feature in this version is 

that the modeling is extended to include a see-through crater as opposed to the earlier model shown in 

Figure 8. This reveals the extent of the damage caused by the impact and how far down the TPS stack 

damage was observed.

Additionally, this model is generated to highlight the capabilities and the ability to enable generating 

such highly complex geometries with good accuracy. The size of the model is relatively large and has

1 891 827 tetrahedral elements and 341 979 nodes. Much larger computational time and core memory 

must be allocated to conduct the analyses using this model compared to the reduced version shown in 

Figure 7. 
NASA/TM—2011-217015 8

Finite Element Modeling and Analyses

The model shown in Figure 7 consists of 31 928 nodes and 485 688 linear tetrahedral 4-node

elements. The model represents a reduced version of the specimen shown in Figure 5(a). It mainly covers 

the impact region (top layer) and the surrounding area. The honeycombs, along with other layers below 

the impact region shown in the specimen photo (Fig. 1), are omitted in the analyses for simplicity 

purposes and to reduce the size of the model. Coupled thermomechanical analyses are conducted under 

combined thermal and mechanical loads. The thermal load is due to the heat generation and the 

mechanical load is due to the maximum attained pressure exerted on the system during reentry of the 

vehicle into Earth’s atmosphere.

The analyses covered only the condition in which the heat flux is the highest. This is to cover

operational impact under the worst-case episode and at the level where the TPS is subjected to the highest 

thermal load possible. Figure 9 offers a representation of the heat flux experienced by the vehicle upon 

reentry (Ref. 13). The mechanical load due to the pressure exerted by the vehicle’s high speed is 

simulated by applying a 21 550-Pa uniform pressure load along the hot face.

The TPS specimen finite element model was contained to simulate a secure attachment to the vehicle.

Mechanical constraints were implemented such that the nodes on the bottom or inner surface were 

restrained from movement in the z-direction, and on the opposite face prescribed pressure loading

boundary conditions were applied normal in the inward direction. Thermal loading was realized by 

assigning a temperature value of 21 °C to the bottom face of the specimen, depicting room-temperature
NASA/TM—2011-217015 9

TABLE I.—TPS MATERIAL (LI–900) PHYSICAL PROPERTIES (REF. 12)

Material Density,

kg/m3

Tensile strength,

kPa

Compression strength,

kPa

Coefficient of thermal 

expansion,

a

cm/cm-°C

Thermal conductivity,

b

W/cm-°C

LI–900 141 Through-thickness, 186

In-plane, 469

Through-thickness, 310

In-plane, 724 In-plane, 5.76×10–7 0.0011394

a

21 to 815 °C. b

at 1 atm and 537.37 °C.

conditions. The thermal load at the top surface was simulated by applying an impingement heat flux. The 

material properties of the TPS, LI–900 (Ref. 11), used in the analysis are shown in Table I. The LI–900 is 

not the material that represents the current system being discussed in this paper; however, it was selected 

because of its similarity to the actual TPS. Figure 10 illustrates the applied boundary conditions. The 

calculations were performed using the general-purpose MARC finite element code (Ref. 12).

Results and Discussion

The finite element analysis results are shown in Figures 11 and 12. Figure 11 represents the thermal 

profile obtained as a result of the orbit reentry impact. As expected, a uniform temperature state 

dominated the top surface exposed to the atmosphere and a through-thickness gradient is noted as the 

thermal profile travels through the material. A maximum temperature of 1500 °C is seen at the top 

surface, and the inner surface maintains a room temperature value of about 21 °C as projected. Additional 

details concerning the thermal profile variations through the thickness of the LI–900 material are clearly 

obvious at the crater regions. 

The stress state generated as a result of the thermal environment experienced during reentry is shown in 

the contour plots represented by Figure 12. Clearly, the crater regions experienced high stress riser

variations as expected (Fig. 12(a)). This is due to the thermal gradient inflicted by the thermal load applied, 

the pressure load, and the material properties disparity with temperature (Fig. 11). However, it must be 

noted that the stress magnitude calculated in these analyses does not reflect the actual magnitude that the 

vehicle would experience during the real episode of reentry; the purpose of these analyses is to demonstrate 

and to verify an analytical methodology only. For a more precise estimation, additional implementations of 

factors pertaining to other materials included in the TPS, the complete data of the thermal and mechanical 

environment, and the entire system material properties must all be accounted for in the analyses.

Figure 12(b) shows a more detailed view of the modeled TPS and additional facts of the stress 

gradient at the craters sections. This confirms the fact that these impact sites could be the trigger points
NASA/TM—2011-217015 10
NASA/TM—2011-217015 11

for potential hazards, which would jeopardize the safety of the vehicle during reentry. In particular, the 

see-through location is the most crucial situation since it would permit the exposure of the internal body 

of the vehicle to a dangerous and high level of heat generated during the reentry period. Such condition is 

a cause for a catastrophic event that would lead to the total destruction of the vehicle. 

Conclusions

This combined microfocus x-ray computed tomography (micro-CT), followed by image segmentation

and processing, with subsequent three-dimensional volume rendering and finite element analysis has 

shown that combining nondestructive evaluation (NDE) and finite element methodology is an effective 

tool to characterize and perform complicated NDE-related computations. It further illustrates an in-depth 

methodology to appraise structural durability issues typically experienced in a damaged thermal 

protection system (TPS) material so improvements in the TPS performance and its capacity to handle 

harsh environments can be made. The CT scanning is utilized as the NDE method to construct a highfidelity three-dimensional finite element model of a complex TPS specimen. The latest advances in 

software technology were instrumental in assisting to build an accurate three-dimensional model with 

ease and with relatively little effort from the user. The finite element mesh size was large, but the section 

model was adequate to represent the damaged TPS. The results showed that the crater regions experience 

high stress risers as anticipated. Clearly, the crater regions’ high stresses were due to the thermal gradient 

inflicted by the heat generated and the pressure loads attained during vehicle reentry into Earth’s 

atmosphere. Additionally, it should be noted that the stress magnitude reported in this study constitutes no 

real estimation of the actual stresses experienced during reentry by the vehicle. A more detailed study is 

needed to accurately estimate such data. 

References

1. Roth, Don J.: NDE Wave and Image Processor Software (NDEWIP). Vol 3, June 2010.

2. ScanFE. Simpleware Ltd., Innovation Centre, University of Exeter, London.

3. Abdul-Aziz, Ali; Baaklini, George; and Bhatt, Ramakrishna: Nondestructive Evaluation of Ceramic 

Matrix Composites Coupled With Finite Element Analyses. SPIE Proceedings Series, vol. 4704, 

2002, pp. 32–39. 

4. Griffin, A.; Knox, C.; and McMillin, S.: Practical Examples: Using Scan Data for Reverse 

Engineering. AUTOFACT ‘97, Society of Manufacturing Engineers, PE98–122, 1997.

5. ScanIP/+FE. Simpleware Ltd., Innovation Centre, University of Exeter, London.

6. Boomsma, K.; and Poulikakos, D.: The Effects of Compression and Pore Size Variations on the Liquid 

Flow Characteristics in Metal Foams. Trans. ASME J. Fluid Eng., vol. 124, 2001, pp. 263–272. 

7. Gibson L.J.; and Ashby M.F.: Cellular Solids: Structure and Properties. Cambridge University Press, 

Cambridge, UK, 1997.

8. Ashby, M.F., et al.: Metal Foams: A Design Guide, Butterworth-Heinemann, Boston, MA, 2000.

9. Banhart, J.: Manufacture, Characterization and Application of Cellular Metals and Metal Foams. 

Prog. Mater. Sci., vol. 46, 2001, pp. 559–632.

10. Yuen, Walter W.; Takara, Ezra; and Cunnington, George: Combined Conductive/Radiative Heat 

Transfer in High Porosity Fibrous Insulation Materials: Theory and Experiment. The 6th ASME–

JSME Thermal Engineering Joint Conference, TED–AJ03–126, 2003.

11. Laub, B.; and Venkatapathy, E.: Thermal Protection System Technology and Facility Needs for 

Demanding Future Planetary Missions. Presented at the International Workshop on Planetary Probe 

Atmospheric Entry and Descent, Trajectory Analysis and Science, Lisbon, Portugal, 2003.

12. MSC/MARC Finite Element Code. The MacNeal-Schwendler Corporation, Costa Mesa, CA, 2010.

13. Arnold, J.O., et al: Nanostructured Thermal Protection Systems for Space Exploration Missions. 

Second International Probe Workshop, NASA Ames Research Center, Moffett Field, CA, 2004.
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Material Characterization and Geometric Segmentation of a Composite Structure Using 

Microfocus X-Ray Computed Tomography Image-Based Finite Element Modeling 

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14. ABSTRACT

This study utilizes microfocus x-ray computed tomography (CT) slice sets to model and characterize the damage locations and sizes in 

thermal protection system materials that underwent impact testing. ScanIP/FE software is used to visualize and process the slice sets, 

followed by mesh generation on the segmented volumetric rendering. Then, the local stress fields around several of the damaged regions are 

calculated for realistic mission profiles that subject the sample to extreme temperature and other severe environmental conditions. The 

resulting stress fields are used to quantify damage severity and make an assessment as to whether damage that did not penetrate to the base 

material can still result in catastrophic failure of the structure. It is expected that this study will demonstrate that finite element modeling 

based on an accurate three-dimensional rendered model from a series of CT slices is an essential tool to quantify the internal macroscopic 

defects and damage of a complex system made out of thermal protection material. Results obtained showing details of segmented images; 

three-dimensional volume-rendered models, finite element meshes generated, and the resulting thermomechanical stress state due to impact 

loading for the material are presented and discussed. Further, this study is conducted to exhibit certain high-caliber capabilities that the 

nondestructive evaluation (NDE) group at NASA Glenn Research Center can offer to assist in assessing the structural durability of such 

highly specialized materials so improvements in their performance and capacities to handle harsh operating conditions can be made.

15. SUBJECT TERMS

Microfocus x-ray; Nondestructive evaluation; Thermal protection system; Finite element; Computed tomography; Orion; Image 

processing; Impact craters 

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