distribution in the 95% safety LUS bound is incorrect. The tail
of the data crosses the 0.05 probability line at –0.42, which
is much lower than where the normal line crosses around
–0.23. These tails indicate there may be some poorly under-
stood aspects of the inversion results (which drive the larger
amount of error in these results) that require further investi-
gation. Smoothed empirical likelihood quantiles can be used
to estimate error quantiles with confidence bounds and do
not assume a specific distribution (Chen and Hall 1993). The
results are presented in Table 5. These 5% quantile estimates
agree with results from the normal probability plots but addi-
tionally provide 95% confidence intervals for the estimates.
5. Conclusions
This paper summarized recent work to improve and validate
the capability to characterize fatigue cracks in metallic mul-
tilayer fastener sites using bolt-hole eddy current (BHEC)
techniques with model-based inversion. Key enhancements
have been made on data preprocessing, model calibration,
liftoff compensation, and the inversion scheme. The updated
approach now addresses crack sizing in titanium, aluminum,
and stainless steel, across multiple frequencies and varying
hole diameters. A novel method was developed to efficiently
build liftoff compensation relationships using limited experi-
ments combined with statistical model fits.
A comprehensive set of fast surrogate models was created
using an improved numerical solver capability, enabling the
simulation of split-D differential eddy current 2D responses for
discontinuities in bolt holes, including corners. Over 2.4 million
measurement simulations were completed in under 200 days.
A comprehensive crack sizing evaluation study was performed,
including 133 unique cracks with verified length and depth
measurements via microscopy, and nearly 1000 BHEC scans
covering a wide range of test conditions.
The results demonstrate improved sizing performance
over the practice of using peak amplitude alone. The crack
length estimates exhibited less error than the crack depth
estimates, although depth is the more critical parameter for
determining appropriate maintenance actions. The 95% safety
limit against undersizing (LUS) bound for corner cracks in
aluminum—within the range where crack removal is feasible—
was estimated to be –0.26 mm. While the average inversion
error for corner cracks in titanium and steel was acceptable,
the tails of the error distributions were too wide to produce
a practical 95% safety LUS bound. Future work is planned to
investigate the root cause for these poor sizing estimates. This
model-based inversion capability has been integrated and
demonstrated with a commercial BHEC instrument.
While significant progress has been made in producing
quality crack dimension estimates using model-based inver-
sion with current BHEC inspection procedure, fundamentally
the BHEC technique was designed to detect the presence of
cracks, not provide the means to size them. One recommenda-
tion is to develop a separate follow-up eddy current procedure
optimized for crack sizing, minimizing error while providing
the maximum utility for the end user.
First, it is difficult to have sensitivity to increasing crack
depth well beyond the depth of penetration of the probe. The
use of lower and multiple frequencies should provide more
capability and improved accuracy over the current single
high-frequency approach. Second, there would be a large
benefit in using a smaller-profile coil to better resolve the ends
of the crack and for assessing much smaller corner cracks. This
is expected to also improve depth estimation. Third, limitations
were discovered in using only a single-point calibration with
one notch size. The calibrated model did not track amplitude
well with increasing crack depth and length. Essentially, if
the application requires accurate sizing beyond 1.2 mm deep
corner cracks, a larger discontinuity size is needed to be part of
the calibration panel and process. In addition, it would also be
advantageous to have notches with different aspect ratios and
to have widths approaching 0.03 mm, which would improve
representation of a crack-like response. These features are not
available in current calibration standards.
Lastly, some model discrepancies were noted, particularly
for stainless steel (17-7PH TH1050), which has a high per-
meability. A surrogate model with greater flexibility to adapt
to a limited set of empirical samples would likely improve
performance—especially for the special case when cracks
are adjacent to a stainless-steel layer. Further development
is needed to design a surrogate model that provides the best
compromise between speed, flexibility, and accuracy.
ACKNOWLEDGMENTS
The authors would like to acknowledge support for this work by the US
Air Force under the contract FA8650-19-C-5218, as well as support for
the manufacture of crack specimens by Dr. Thomas Mills of Analytical
Processes/Engineered Solutions (AP/ES) software development by Sean
Corley (formerly of TRI Austin) sample manufacture, sample verification,
and data acquisition by John Nagel (formerly of TRI Austin), Cody Morrow
(formerly of TRI Austin), Jameson Pitcheralle (TRI Austin) and general
support in the eddy current technique from ASNT NDT Level III (ET) Mark
Keiser (TRI Austin). The UniWest EVi eddy current inspection system with
an ECS-5 BHEC scanner was used to acquire all experimental data for the
program.
REFERENCES
Aldrin, J. C., and D. S. Forsyth. 2017. “NDE characterization capability eval-
uation.” Materials Evaluation 75 (7): 915–929.
Aldrin, J. C., M. Keiser, D. Motes, J. Flores-Lamb, D. S. Forsyth, H. A.
Sabbagh, E. Sabbagh, R. K. Murphy, R. Mooers, C. Henry, and E. A.
Lindgren. 2019. “Progress and Challenges of Inverse Methods for Sizing
Cracks in Multilayer Bolt-holt Eddy Current Inspections.” In Electromag-
netic Nondestructive Evaluation (XXII), ed. A. Tamburrino, Y. Deng, and S.
Chakrapani, 92–97. IOS Press. https://doi.org/10.3233/SAEM190017.
Aldrin, J. C., and E. A. Lindgren. 2018. “The Need and Approach for Char-
acterization US Air Force Perspectives on Materials State Awareness.” AIP
Conference Proceedings 1949: 020004. https://doi.org/10.1063/1.5031501.
Aldrin, J. C., H. A. Sabbagh, E. Sabbagh, R. K. Murphy, M. Keiser, D. S.
Forsyth, and E. A. Lindgren. 2014. “Model-based inverse methods for bolt-
holt eddy current (BHEC) inspections.” AIP Conference Proceedings 1581:
1433–1440. https://doi.org/10.1063/1.4864990.
A U G U S T 2 0 2 5 M AT E R I A L S E V A L U AT I O N 55
Aldrin, J. C., H. A. Sabbagh, L. Zhao, E. Sabbagh, R. K. Murphy, M. Keiser,
J. Flores-Lamb, D. S. Forsyth, D. Motes, E. A. Lindgren, and R. Mooers.
2016. “Model-based inverse methods for sizing cracks of varying shape and
location in bolt-hole eddy current (BHEC) inspections.” AIP Conference
Proceedings 1706: 090020. https://doi.org/10.1063/1.4940557.
Annis, C., J. C. Aldrin, and H. A. Sabbagh. 2015. “What is missing in
nondestructive testing capability evaluation?” Materials Evaluation 73 (1):
1–11.
ASTM. 2014. ASTM E2782-11: Standard Guide for Measurement Systems
Analysis (MSA). ASTM International: West Conshohocken, PA. https://doi.
org/10.1520/E2782-11.
ASTM. 2021. ASTM E3023-15: Standard Practice for Probability of Detection
Analysis for â Versus a Data. ASTM International: West Conshohocken, PA.
https://doi.org/10.1520/E3023-15.
Auld, B. A., and J. C. Moulder. 1999. “Review of Advances in Quantitative
Eddy Current Nondestructive Evaluation.” Journal of Nondestructive Evalu-
ation 18 (1): 3–36. https://doi.org/10.1023/A:1021898520626.
Bao, Y., Y. Liu, J. Qiu, and J. Song. 2025. “Uncertainty propagation for
MAPoD in eddy current NDT by polynomial chaos–kriging.” Nondestruc-
tive Testing and Evaluation 40 (5): 1854–1876. https://doi.org/10.1080/
10589759.2024.2366317.
Chen, S. X., and P. Hall. 1993. “Smoothed empirical likelihood confidence
intervals for quantiles.” Annals of Statistics 21 (3): 1166–1181. https://doi.
org/10.1214/aos/1176349256.
Førli, O., et al. 1998. Guidelines for NDE Reliability Determination and
Description (Technical Report 394). Nordtest: Espoo, Finland. http://
nordtest.info/images/documents/nt-technical-reports/NT%20TR%20394_
Guideline%20for%20NDE%20Reliability%20Determination%20and%20
Description_Nordtest%20Technical%20Report.pdf.
Hughes, R. R., and B. W. Drinkwater. 2021. “Exploring high-frequency
eddy-current testing for sub-aperture defect characterisation using
parametric-manifold mapping.” NDT &E International 124: 102534.
https://doi.org/10.1016/j.ndteint.2021.102534.
Lindgren, E. A., and J. S. Knopp. 2016. “US Air Force Perspective on Vali-
dated NDE Past, Present, and Future.” AIP Conference Proceedings 1706:
020002. https://doi.org/10.1063/1.4940448.
Lindgren, E. A., J. S. Knopp, J. C. Aldrin, G. J. Steffes, and C. F. Buynak.
2007. “Aging Aircraft NDE: Capabilities, Challenges, and Oppor-
tunities.” AIP Conference Proceedings 894: 1731–1738. https://doi.
org/10.1063/1.2718173.
Liu, X., Y. Deng, Z. Zeng, L. Udpa, and J. S. Knopp. 2008. “Model Based
Inversion Using the Element-Free Galerkin Method.” Materials Evaluation
66 (7): 740–746.
Lozev, M., D. Hodgkinson, R. Spencer, and B. Grimmett. 2005. “Validation
of Current Approaches for Girth Weld Defect Sizing Accuracy by Pulse-
Echo, Time-of-Flight Diffraction, and Phased-Array Mechanized Ultrasonic
Testing Methods.” Materials Evaluation 63 (5): 505–510.
Mandache, C., M. Khan, A. Fahr, and M. Yanishevsky. 2011. “Numerical
modelling as a cost-reduction tool for probability of detection of bolt hole
eddy current testing.” Nondestructive Testing and Evaluation 26 (1): 57–66.
https://doi.org/10.1080/10589751003770118.
Oneida, E. K., E. B. Shell, J. C. Aldrin, H. A. Sabbagh, E. Sabbagh, and
R. K. Murphy. 2017. “Characterizing Surface-Breaking Cracks through Eddy
Current NDE and Model-Based Inversion.” Materials Evaluation 75 (7):
915–929.
Sabbagh, H. A., R. K. Murphy, E. H. Sabbagh, J. C. Aldrin, and J. S. Knopp.
2013. Computational Electromagnetics and Model-Based Inversion: A
Modern Paradigm for Eddy-Current Nondestructive Evaluation. Springer:
New York, NY. https://doi.org/10.1007/978-1-4419-8429-6.
Sabbagh, L. D., and H. A. Sabbagh. 1988. “Eddy-Current Modeling and
Flaw Reconstruction.” Journal of Nondestructive Evaluation 7: 95–110.
https://doi.org/10.1007/BF00565780.
Shell, E. B., J. C. Aldrin, H. A. Sabbagh, E. Sabbagh, R. K. Murphy, S.
Mazdiyasni, and E. A. Lindgren. 2015. “Demonstration of Model-Based
Inversion of Electromagnetic Signals for Crack Characterization.” AIP
Conference Proceedings (1650): 484–493. https://doi.org/10.1063/1.4914645.
US Department of Defense. 2009. Department of Defense Handbook:
Nondestructive Evaluation System Reliability Assessment (MIL-HDBK-
1823A). Standardization Order Desk: Philadelphia, PA. https://statistical
-engineering.com/wp-content/uploads/2017/10/MIL-HDBK-1823A2009.
pdf.
Yanishevsky, M., M. Martinez, C. Mandache, M. Khan, A. Fahr, and D.
Backman. 2010. “Artificial seeding of fatigue cracks in NDI reference
coupons.” Insight (Northampton) 52 (12): 664–671. https://doi.org/10.1784/
insi.2010.52.12.664.
Yusa, N. 2009. “Development of Computational Inversion Techniques to
Size Cracks from Eddy Current Signals.” Nondestructive Testing and Evalu-
ation 24 (1–2): 39–52. https://doi.org/10.1080/10589750802195469.
ME
|
CRACKSIZING
56
M AT E R I A L S E V A L U AT I O N A U G U S T 2 0 2 5
Previous Page Next Page