• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.46-51
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• 2015

Stainless steel is a popular structural materials for liquid-hydrogen storage containers and piping components for transporting high-temperature fluids because of its superior material properties such as high strength and high corrosion resistance at elevated temperatures. In general, tungsten inert gas (TIG) arc welding is used for bonding stainless steel. However, it is often reported that the thermal fatigue cracks or initial defects in stainless steel after welding decreases the reliability of the material. The objective of this paper is to clarify the characteristics of ultrasonic guided wave propagation in relation to a change in the initial crack length in the welding zone of stainless steel. For this purpose, three specimens with different artificial defects of 5 mm, 10 mm, and 20 mm in stainless steel welds were prepared. By considering the thickness of s stainless steel pipe, special attention was given to both the L(0,1) mode and L(0,2) mode in this study. It was clearly found that the L(0,2) mode was more sensitive to defects than the L(0,1) mode. Based on the results of the L(0,1) and L(0,2) mode analyses, the magnitude ratio of the two modes was more effective than studying each mode when evaluating defects near the welded zone of stainless steel because of its linear relationship with the length of the artificial defect.

• Structural Engineering and Mechanics
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• v.65 no.2
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• pp.129-139
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• 2018

Post-tensioning (PT) tendons are commonly used for the assembly of modularized concrete members, and tension is applied to the tendons during construction to facilitate the integrated behavior of the members. However, the tension in a PT tendon decreases over time due to steel corrosion and concrete creep, and consequently, the stress on the anchor head that secures the PT tendon also diminishes. This study proposes an automatic detection system to identify tension reduction in a PT tendon using pulsed-eddy-current (PEC) measurement. An eddy-current sensor is installed on the surface of the steel anchor head. The sensor creates a pulsed excitation to the driving coil and measures the resulting PEC response using the pick-up coil. The basic premise is that the tension reduction of a PT tendon results in stress reduction on the anchor head surface and a change in the PEC intensity measured by the pick-up coil. Thus, PEC measurement is used to detect the reduction of the anchor head stress and consequently the reduction of the PT tendon force below a certain threshold value. The advantages of the proposed PEC-based tension-reduction-detection (PTRD) system are (1) a low-cost (< $ 30), low-power (< 2 Watts) sensor, (2) a short inspection time (< 10 seconds), (3) high reliability and (4) the potential for embedded sensing. A 3.3 m long full-scale monostrand PT tendon was used to evaluate the performance of the proposed PTRD system. The PT tendon was tensioned to 180 kN using a custom universal tensile machine, and the tension was decreased to 0 kN at 20 kN intervals. At each tension, the PEC responses were measured, and tension reduction was successfully detected.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.657-665
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• 2021

Nondestructive evaluation methods play an important role in ensuring component integrity and safety in many industries. Operator fatigue can play a critical role in the reliability of such methods. This is important for inspecting high value assets or assets with a high consequence of failure, such as aerospace and nuclear components. Recent advances in convolution neural networks can support and automate these inspection efforts. This paper proposes using residual neural networks (ResNets) for real-time detection of corrosion, including iron oxide discoloration, pitting and stress corrosion cracking, in dry storage stainless steel canisters housing used nuclear fuel. The proposed approach crops nuclear canister images into smaller tiles, trains a ResNet on these tiles, and classifies images as corroded or intact using the per-image count of tiles predicted as corroded by the ResNet. The results demonstrate that such a deep learning approach allows to detect the locus of corrosion via smaller tiles, and at the same time to infer with high accuracy whether an image comes from a corroded canister. Thereby, the proposed approach holds promise to automate and speed up nuclear fuel canister inspections, to minimize inspection costs, and to partially replace human-conducted onsite inspections, thus reducing radiation doses to personnel.