Dr. S. Thirunavukkarasu | AI in Engineering | Best Researcher Award

Dr. S. Thirunavukkarasu | Indira Gandhi Centre for Atomic Research | India

Dr. S. Thirunavukkarasu research focuses on quantitative nondestructive evaluation (NDE), finite element (FE) modeling, digital signal and image processing, and the development of innovative sensors and instrumentation for advanced inspection applications. His work emphasizes multi-parametric linear and nonlinear regression, radial basis function (RBF), and multidimensional RBF neural networks for accurate flaw sizing in eddy current testing. He has contributed to FE modeling of electromagnetic NDE phenomena, including the optimization of remote field eddy current probe parameters for ferromagnetic steam generator tube inspections and modeling of magnetic flux leakage considering nonlinear magnetic permeability. His studies extend to the simulation of pulsed and sweep frequency eddy current methods to improve detection efficiency. Additionally, his research in wavelet transform–based digital signal processing enhances the interpretation of eddy current signals from complex regions such as bends and support plate intersections. He has also advanced in-house development of remote field eddy current techniques for the inspection of modified 9Cr-1Mo steel steam generator tubes. His computational expertise includes MATLAB, Python, and LabVIEW, alongside specialized software such as COMSOL, FEMM, and CIVA for modeling and simulation in electromagnetic and NDE applications.

Profile: Orcid

Featured Publications

Arun, A. D., Rajiniganth, M. P., Chandra, S., & Thirunavukkarasu, S. (2025). A numerical model of parallel disc capacitor probe used in nondestructive dielectric permittivity evaluation by algebraic topological method. International Journal of Applied Electromagnetics and Mechanics, 2025-09.

Sharatchandra Singh, W., Haneef, T. K., Thirunavukkarasu, S., & Kumar, A. (2025). In-situ measurement of tensile deformation-induced magnetic fields in high strength low alloy steels using GMR based metal magnetic memory technique. International Journal of Applied Electromagnetics and Mechanics, 2025-09-10.

Arun, A. D., Chandra, S., Thirunavukkarasu, S., Rajiniganth, M. P., Malathi, N., & Sivaramakrishna, M. (2025). A novel algebraic topological method-based approach for evaluating stored electrostatic energy and 3D Maxwellian capacitance. Journal of Electrostatics, 2025-06.

Thirunavukkarasu, S., Kumar, A., Martin, J. P., Harini, T., Reddy, S., Emil, S., & Balu, C. (2025). Automated detection of defects in eddy current inspection data using machine learning methods. International Journal of Applied Electromagnetics and Mechanics, 2025-06-03.

Balakrishnan, S., Das, C. R., Thirunavukkarasu, S., & Kumar, A. (2025). In-situ hardness evaluation of hard-faced coatings through eddy current NDE. International Journal of Applied Electromagnetics and Mechanics, 2025-05-23.

Vijayachandrika, T., Arjun, V., Thirunavukkarasu, S., & Kumar, A. (2025). Design, fabrication, and characterization of staggered array radial coil RFEC probe for small diameter ferritic steel tube. IEEE Sensors Journal, 2025-05-01.