John C. Aldrin

Expertise

• NDE Modeling and Simulation
• NDE Assisted Data Analysis (ADA) and AI/ML Inverse Methods in NDE
• NDE and SHM Reliability Assessment and Model-assisted Probably of Detection (MAPOD) Evaluation
• NDE 4.0 (Digital Twin)
• Technology Transition

Recognition and Awards

• Fellow, American Society of Nondestructive Testing (ASNT)
• NASA Engineering and Safety Center (NESC) Engineering Excellence Award (2009)
• 2010 TTCP (The Technical Cooperation Program) Team Achievement Award (for Model-Based Methods for Reducing Cost Associated with POD Studies)
• Associate Technical Editor of Materials Evaluation (since 2013) and Journal of Nondestructive Evaluation (since 2022)

Selected publications

• Aldrin, J., Achenbach, J. D., Andrew, G., P’an, C., Grills, B., Mullis, R. T., Spencer, F. W., Golis, M., “Case Study for the Implementation of an Automated Ultrasonic Technique to Detect Fatigue Cracks in Aircraft Weep Holes,” Materials Evaluation, Vol. 59, n 11, pp.1313-1319, (2001). [Best paper award, 2001].
• Aldrin, J. C., Knopp, J. S., “Crack Characterization Method with Invariance to Noise Features for Eddy Current Inspection of Fastener Sites”, Journal of Nondestructive Evaluation, Vol. 25, n 4, pp. 165-181, (2006).
• Aldrin, J. C., Blodgett, M. P., Lindgren, E. A., Steffes, G. J., and Knopp, J. S., “Scattering of obliquely incident shear waves from a cylindrical cavity”, Journ. Acoust Soc. America, 129, pp. 3661-3675 (2011).
• Aldrin, J., C., Forsyth, D. S., and Welter, J. T., “Design and Demonstration of Automated Data Analysis Algorithms for Ultrasonic Inspection of Complex Composite Panels with Bonds,” QNDE, Vol. 1706, p. 120006, AIP Publishing, (2016).
• Aldrin, J. C., “Intelligence Augmentation and Human Machine Interface Best Practices for NDT 4.0 Reliability”, Materials Evaluation, 78 (7), (2020) pp. 869-879. DOI: 10.32548/2020.me04133.