A novel ultrasonic non-destructive testing methodology to monitor fatigue crack growth in compact tension specimens Saju T. Abraham, M. Nani Babu, B. Venkatraman Review of Scientific Instruments, 2023 Detection and evaluation of fatigue cracks in structural materials are extremely important for life prediction analysis as part of the structural integrity procedure. In this article, we present a novel ultrasonic measurement methodology, based on the diffraction of elastic waves at the crack tips, to monitor the fatigue crack growth near the threshold regime in compact tension specimens at different load ratios. The diffraction phenomenon of ultrasonic waves from the crack tip is demonstrated using a finite element 2D wave propagation simulation. The applicability of this methodology has also been contrasted with that of the conventional direct current potential drop method. In addition, the crack morphology obtained in the ultrasonic c-scan imaging showed a variation in the crack propagation plane as a function of the cyclic loading parameters. The results suggest that this novel methodology is sensitive to fatigue cracks and can form the basis of in situ ultrasonic-based crack measurements in metallic and non-metallic materials.
An experimental investigation on the combined effect of plastic deformation and grain size variation on the acoustic nonlinearity parameter Saju T. Abraham, C. Teena Mouni, S. K. Albert, A. Sagdeo, Krishnan Balasubramaniam, B. Venkatraman Review of Scientific Instruments, 2023 The combined effect of grain size variation and plastic deformation on the acoustic nonlinearity parameter has been investigated in an austenitic stainless-steel material of grade 304. The nonlinear behavior of this parameter with grain growth has deviated to linear fit with deformation. This is due to the interaction of elastic waves with the strain-induced dislocation substructure in the grains. The normalized mean square strain of the deformed specimens has been estimated through angle dispersive x-ray diffraction studies using a synchrotron source, and this has been correlated with the change in the acoustic non-linearity parameter with deformation. The nonlinearity parameter is found to be very sensitive to the plastic deformation even in the presence of grain size variations. The results infer that the variations in the nonlinearity parameter can be used to have an estimate of the extent of localized deformations often occurring during the fabrication of metallic components.
A machine learning approach to nonlinear ultrasonics for classifying annealing conditions in austenitic stainless steel Saju T. Abraham, Manju Mohan, Pandian Chelliah, Krishnan Balasubramaniam, B Venkatraman Journal of Applied Physics, 2022 This paper explores the feasibility of machine learning algorithms on nonlinear ultrasonics for classification of the austenitic stainless-steel material subjected to different annealing conditions. The material that is isothermally annealed at 1323 K for different soaking times showed a marginal variation in its nonlinearity parameter at larger mean grain sizes. The grain growth during annealing followed the Arrhenius type equation fairly well, which has been verified using a genetic algorithm approach. The machine learning algorithms are trained using features such as the ratio of the harmonic amplitudes, root-mean-square value, and the phase difference between the fundamental and second harmonic components derived from the nonlinear ultrasonic response. Upon evaluating the performance of decision tree and ensemble learning algorithms in the classification of annealed materials, it was observed that the LPBoost classifier has the highest accuracy of 97%. According to the results, it is concluded that a machine learning strategy based on a minimal number of features can effectively classify specimens that are otherwise indistinguishable in their nonlinear response. This research takes a step forward to the automation of non-destructive testing toward Industrial Revolution 4.0. The results also pointed out the necessity of parameter fusion in non-destructive decision making.
Effect of grain size distribution on the acoustic nonlinearity parameter Saju T. Abraham, S. Shivaprasad, C. R. Das, S. K. Albert, B. Venkatraman, Krishnan Balasubramaniam Journal of Applied Physics, 2020 The effect of grain size distribution on the measured acoustic nonlinearity of polycrystalline engineering materials is investigated. Results are provided for two austenitic stainless steel materials with comparable mean grain sizes and distinct distribution widths assuming equiaxed grains and random crystallographic orientation. The distribution width is shown to influence the nonlinearity parameter considerably. On the material with a wider distribution, a reduced nonlinearity was noted, and comparable trends were also noted for different frequencies investigated. The results predict that the existing models that account for only the mean grain size when characterizing material degradations need to be modified more comprehensively to include the role of grain size distribution.
Characterisation of heterogeneous microstructure in large forged products using nonlinear ultrasonic method Saju T. Abraham, S. Shivaprasad, C.R. Das, S. K. Albert, B. Venkatraman, Krishnan Balasubramaniam Materials Science and Technology United Kingdom, 2020 A comparative study between the ultrasonic attenuation and the nonlinearity is presented for the characterisation of microstructure in large dimension forgings. Results are provided for two austenitic stainless steel forgings of AISI type 304L with a diameter 200 mm, where microscopic observations reveal abnormal grain growth near the surface of one of the forgings. Frequency dependence of the nonlinearity parameter is used to discern variations in grain size in these forgings more precisely than attenuation measurements. The distribution of grain size is shown to have a significant influence on the nonlinearity parameter. Relative changes in the nonlinearity parameter with applied frequency were correlative with the microstructural variations in both the forgings.
Time of flight diffraction testing of austenitic stainless steel weldments at elevated temperatures Materials Evaluation, 2008
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A machine learning approach to nonlinear ultrasonics for classifying annealing conditions in austenitic stainless steel ST Abraham, M Mohan, P Chelliah, K Balasubramaniam, B Venkatraman Journal of Applied Physics 132 (11) , 2022 2022 Citations: 7
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Ultrasonic study of elastic anisotropy of unidirectional Rochelle salt single crystals grown using the Sankaranarayanan-Ramasamy method S Singaravadivelu, A Uthayakumar, ST Abraham Journal of Crystal Growth 478, 146-151 , 2017 2017 Citations: 3
Diffusion bonding of PZT disc to nickel wear plate for fabrication of high temperature under-sodium ultrasonic transducers I Lakshmigandhan, ST Abraham, C Asokane, MR Jeyan, ASR Murthy, ... Nuclear Engineering and Design 433, 113832 , 2025 2025 Citations: 2
An experimental investigation on the combined effect of plastic deformation and grain size variation on the acoustic nonlinearity parameter ST Abraham, CT Mouni, SK Albert, A Sagdeo, K Balasubramaniam, ... Review of Scientific Instruments 94 (2) , 2023 2023 Citations: 2
Application of Time of Flight Diffraction Technique for Imaging Cracks in Rod Specimens ST Abraham, B Venkatraman, B Raj, SC Chetal Materials Evaluation 71 (4) , 2013 2013 Citations: 2
Diffusion bonding of piezoelectric crystal to metal wear plate T Gnanasekaran, I Lakshmi Gandhan, C Asokane, MR Jeyan, ... US Patent 12,439,824 , 2025 2025
Diffusion bonding of piezoelectric crystal to metal wear plate T Gnanasekaran, I Lakshmi Gandhan, C Asokane, MR Jeyan, ... IN Patent 508,553 , 2024 2024
Diffusion Bonding of Piezoelectric Crystal to Metal Wear Plate T Gnansekaran, I Lakshmi Gandhan, C Asokane, MR Jeyan, ST Abraham EP Patent 3,948,967 , 2023 2023
NDE during fabrication of blanket sub assemblies for prototype fast breeder reactor YRC Murthy, B Ravinder, B Kamalesh Kumar, C Phani Babu, RK Mistry, ... Proceedings of the twenty-fifth national seminar and international … , 2015 2015
Probability of defect detection in conventional and advanced ultrasonic testing for different austenitic stainless steel weld joint configurations K Murugan, D Chitra, ST Abraham, MV Kuppusamy, ... Proceedings of the twenty-fifth national seminar and international … , 2015 2015
