• Journal of the Korean Society of Safety
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• v.36 no.4
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• pp.1-11
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• 2021

Piping systems comprising pumps and valves are essential in the power plant, oil, and defense industry. Their purpose includes a stable supply of the working fluid or ensuring the target system's safe operation. However, piping system accidents due to leakage of toxic substances, explosions, and natural disasters are prevalent In addition, with the limited maintenance personnel, it becomes difficult to detect, isolate, and reconfigure the damage of the piping system and recover the unaffected area. An autonomous recovery piping system can play a vital role under such circumstances. The autonomous recovery algorithms for the piping system can be divided into low-pressure control algorithms, hydraulic resistance control algorithms, and flow inventory control algorithms. All three methods include autonomous opening/closing logic to isolate damaged areas and recovery the unaffected area of piping systems. However, because each algorithm has its strength and weakness, appropriate application considering the overall design, vital components, and operating conditions is crucial. In this regard, preliminary research on algorithm's working principle, its design procedures, and expected damage scenarios should be accomplished. This study examines the characteristics of algorithms, the design procedure, and working logic. Advantages and disadvantages are also analyzed through simulation results for a simplified piping system.

• International journal of steel structures
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• v.18 no.4
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• pp.1200-1209
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• 2018

In this study, a probabilistic framework of the damage assessment of pipelines subjected to extreme hazard scenario was developed to mitigate the risk and enhance design reliability. Nonlinear 3D finite element models of T-joint systems were developed based on experimental tests with respect to leakage detection of black iron piping systems, and a damage assessment analysis of the vulnerability of their components according to nominal pipe size, coupling type, and wall thickness under seismic wave propagations was performed. The analysis results showed the 2-inch schedule 40 threaded T-joint system to be more fragile than the others with respect to the nominal pipe sizes. As for the coupling types, the data indicated that the probability of failure of the threaded T-joint coupling was significantly higher than that of the grooved type. Finally, the seismic capacity of the schedule 40 wall thickness was weaker than that of schedule 10 in the 4-inch grooved coupling, due to the difference in the prohibition of energy dissipation. Therefore, this assessment can contribute to the damage detection and financial losses due to failure of the joint piping system in a liquid pipeline, prior to the decision-making.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.11 no.2
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• pp.61-67
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• 2015

3D FEM modeling based on 3D CAD data has been performed to evaluate the efficiency of CP system in a real operating nuclear power plant. The results of it successfully produced sophisticated profiles of electrolytic potential and current distributions in the soil of an interested area. This technology is expected to be a breakthrough for detection technology of damages on buried pipes when it comes into combining with a brand of area potential earth current (APEC) and ground penetrated radar (GPR) technologies. 2D current distribution and 2D current vectors on the earth surface from the APEC survey will be used as boundary conditions with exact 3D geometry data resulting in visualization of locations and extents of corrosion damages on the buried pipes in nuclear power plants.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.2
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• pp.18-24
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• 2020

When a damage occurs in the nuclear fuel burning in the reactor, fission products that should be in the nuclear fuel rod are released into the reactor coolant. In this case, sipping test, a series of non-destructive inspection methods, are used to find leakage in nuclear fuel assemblies during the power plant overhaul period. In addition, the sipping test is also used to check the integrity of the spent fuel for moving to an intermediate dry storage, which is carried out as the first step of nuclear decommissioning, . In this paper, the principle and characteristics of the sipping test are described. The structure of the sipping inspection equipment is largely divided into a suction device that collects fissile material emitted from a damaged assembly and an analysis device that analyzes their nuclides. In order to make good use of the sipping technology, the radioactive level behavior of the primary system coolant and major damage mechanisms in the event of nuclear fuel damage are also introduced. This will be a reference for selecting an appropriate sipping method when dismantling a nuclear power plant in the future.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.317-321
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• 2008

Piping in the Nuclear Power plants (NPP) are mostly consisted of carbon steel pipe. The wall thinning defect is mainly occurred by the affect of the flow accelerated corrosion (FAC) of fluid which flows in carbon steel pipes. This type of defect becomes the cause of damage or destruction of piping. Therefore, it is very important to measure defect which is existed not only on the welding partbut also on the whole field of pipe. Over the years, Infrared thermography (IRT) has been used as a non destructive testing methods of the various kinds of materials. This technique has many merits and applied to the industrial field but has limitation to the materials. Therefore, this method was combined with lock-in technique. So IRT detection resolution has been progressively improved using lock-in technique. In this paper, the quantitative analysis results of the location and the size of wall thinning defect that is artificially processed inside the carbon steel pipe by using IRT are obtained.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.155-162
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• 2019

To reduce the secondary damage caused by leakage accidents in plant piping systems, a constant surveillance system is necessary. To ensure leaks are promptly addressed, the surveillance system should be able to detect not only the leak itself, but also the location of the leak. Recently, research to develop new methods has been conducted using cameras to detect leakage and to estimate the location of leakage. However, existing methods solely estimate whether a leak exists or not, or only provide two-dimensional coordinates of the leakage location. In this paper, a method using multiple cameras to detect leakage and estimate the three-dimensional coordinates of the leakage location is presented. Leakage is detected by each camera using MADI(Moving Average Differential Image) and histogram analysis. The two-dimensional leakage location is estimated using the detected leakage area. The three-dimensional leakage location is subsequently estimated based on the two-dimensional leakage location. To achieve this, the coordinates (x, z) for the leakage are calculated for a horizontal section (XZ plane) in the monitoring area. Then, the y-coordinate of leakage is calculated using a vertical section from each camera. The method proposed in this paper could accurately estimate the three-dimensional location of a leak using multiple cameras.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.12 no.1
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• pp.93-100
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• 2016

Since the sodium-cooled fast reactor is operated in a hostile environment due to the use of liquid sodium as its coolant, advanced techniques for in-service inspection are required to periodically verify the integrity of the reactor. This paper presents the development of in-service inspection techniques for Proto-type Generation IV Sodium-cooled Fast Reactor. First, the 10 m long plate-type ultrasonic waveguide sensor has been developed for in-service inspection of reactor internals, and its feasibility was verified through several under-water and under-sodium experiments. Second, the combined inspection system for in-service inspection of ferromagnetic steam generator tubes has been developed. The remote field eddy current testing and magnetic flux leakage testing can be conducted simultaneously by using the developed inspection system, and the detectability was demonstrated through several damage detection experiments. Finally, the electro-magnetic acoustic transducer which can withstand high temperature and be installable in the remote operated vehicle has been developed for in-service inspection of the reactor vessel, and its detectability was investigated through damage detection experiments.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1557-1562
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• 2009

In the hydraulic room of a forging press machine, a system which can detect and prevent risks at its early stage is needed because there may be a leakage due to the damage of the connection parts of the piping which can endanger human life and mechanical damage. In this paper, the system to automatically recognize a leakage of hydraulic fluid in terms of using the pan/tilt camera from a remote place is implemented. It finds the bounding boxes which are recognized with object regions in the process of labeling and detects the proper leakage regions of hydraulic fluid with the ratios of width and height of the bounding boxes and compactness of the leakage shape. Also, it performs noise removal and calibration for transition and rotation of image as a preprocessing process. The experimental results show that the proposed system has been verified to detect the leakage regions accurately in various sources of light.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.688-706
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• 2024

Austenitic stainless steels (ASS) are extensively employed in various sectors such as nuclear, power, petrochemical, oil and gas because of their excellent structural strength and resistance to corrosion. SS304 and SS316 are the predominant choices for piping, pressure vessels, heat exchangers, nuclear reactor core components and support structures, but they are susceptible to stress corrosion cracking (SCC) in chloride-rich environments. Over the course of several decades, extensive research efforts have been directed towards evaluating SCC using diverse methodologies and models, albeit some uncertainties persist regarding the precise progression of cracks. This review paper focuses on the application of Acoustic Emission Technique (AET) for assessing SCC damage mechanism by monitoring the dynamic acoustic emissions or inelastic stress waves generated during the initiation and propagation of cracks. AET serves as a valuable non-destructive technique (NDT) for in-service evaluation of the structural integrity within operational conditions and early detection of critical flaws. By leveraging the time domain and time-frequency domain techniques, various Acoustic Emission (AE) parameters can be characterized and correlated with the multi-stage crack damage phenomena. Further theories of the SCC mechanisms are elucidated, with a focus on both the dissolution-based and cleavage-based damage models. Through the comprehensive insights provided here, this review stands to contribute to an enhanced understanding of SCC damage in stainless steels and the potential AET application in nuclear industry.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.