• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.552-568
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• 2020

After long-term service in deep ocean, pipelines are usually suffered from corrosions, which may greatly influence the Vortex-Induced Vibration (VIV) behavior of pipes. Thus, we investigate the VIV of defective pipelines. The geometric nonlinearity due to large deformation of pipes and nonlinearity in vortex-induced force are simulated. This nonlinear vibration system is simulated with finite element method and solved by direct integration method with incremental algorithm. Two kinds of defects, corrosion pits and volumetric flaws, and their effects of depth and range on VIV responses are investigated. A new finite element is developed to simulate corrosion pits. Defects are found to aggravate VIV displacement response only if environmental flow rate is less than resonance flow rate. As the defect depth grows, the stress responses increase, however, the increase of the defect range reduces the stress response at corroded part. The volumetric flaws affect VIV response stronger than the corrosion pits.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.76-83
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• 2023

Recently, the development of computer vision with deep learning has made object detection using images applicable to diverse fields, such as medical care, manufacturing, and transportation. The manufacturing industry is saving time and money by applying computer vision technology to detect defects or issues that may occur during the manufacturing and inspection process. Annotations of collected images and their location information are required for computer vision technology. However, manually labeling large amounts of images is time-consuming, expensive, and can vary among workers, which may affect annotation quality and cause inaccurate performance. This paper proposes a process that can automatically collect annotations and location information for images using eXplainable AI, without manual annotation. If applied to the manufacturing industry, this process is thought to save the time and cost required for image annotation collection and collect relatively high-quality annotation information.

• Journal of the Microelectronics and Packaging Society
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• v.29 no.4
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• pp.89-94
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• 2022

Thermoelectric materials can directly convert a temperature gradient to an electrical energy and vice-versa, and their performance is determined by the electrical conductivity, Seebeck coefficient, and thermal conductivity. However, it is difficult to establish an effective strategy for enhancing performance since electrical conductivity, Seebeck coefficient, and thermal conductivity are strongly dependent on the composition, crystal structure, and electronic structure of the material, and show a correlation with each other. Herein, based on the understanding of the formulas related to the performance of thermoelectric materials, we provide a methodology to establish feasible defect engineering strategies of thermal conductivity reduction for improving the performance of thermoelectric materials in connection with the experimental results.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2412-2420
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• 2024

The International Atomic Energy Agency (IAEA) mandates safeguards to ensure non-proliferation of nuclear materials. Among inspection techniques used to detect partial defects within spent nuclear fuel (SNF), gamma emission tomography (GET) has been reported to be reliable for detection of partial defects on a pin-by-pin level. Conventional GET, however, is limited by low detection efficiency due to the high density of nuclear fuel rods and self-absorption. This paper proposes a new type of GET named Spent Fuel Internal Tomography (SFIT), which can acquire sinograms at the guide tube. The proposed device consists of the housing, shielding, C-shaped collimator, reflector, and gadolinium aluminum gallium garnet (GAGG) scintillator. For accurate attenuation correction, the source-distinguishable range of the SFIT device was determined using MC simulation to the region away from the proposed device to the second layer. For enhanced inspection accuracy, a proposed specific source-discrimination algorithm was applied. With this, the SFIT device successfully distinguished all source locations. The comparison of images of the existing and proposed inspection methods showed that the proposed method, having successfully distinguished all sources, afforded a 150 % inspection accuracy improvement.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.593-594
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.551-552
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.67-68
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• 2012

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1076-1077
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• 2007

CMS(Condition Monitoring System) is a useful tool to predict the defect of machine condition, for example, Motor, Bearing, Gear, Fan, etc. And, recently CMS is very important on plant. In this paper, describe the bearing electric arcing with example.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.10a
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• pp.218-218
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• 2003

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1461-1462
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• 2010