• Nuclear Engineering and Technology
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• 제55권4호
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• pp.1528-1539
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• 2023

Since the leakage of sodium in an SFR (sodium-cooled fast reactor) causes an explosion upon reaction with air and water, sodium leakages represent an important safety issue. In this study, a novel technique for improving the reliability of sodium leakage detection applying DDVR (dynamic data validation and reconciliation) is proposed and verified to resolve this technical issue. DDVR is an approach that aims to improve the accuracy of a target system in a dynamic state by minimizing random errors, such as from the uncertainty of instruments and the surrounding environment, and by eliminating gross errors, such as instrument failure, miscalibration, or aging, using the spatial redundancy of measurements in a physical model and the reliability information of the instruments. DDVR also makes it possible to estimate the state of unmeasured points. To validate this approach for supporting sodium leakage detection, this study applies experimental data from a sodium leakage detection experiment performed by the Korea Atomic Energy Research Institute. The validation results show that the reliability of sodium leakage detection is improved by cooperation between DDVR and hardware measurements. Based on these findings, technology integrating software and hardware approaches is suggested to improve the reliability of sodium leakage detection by presenting the expected true state of the system.

• 융합보안논문지
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• 제19권2호
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• pp.3-9
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• 2019

지속적으로 발생하는 기술 유출 사고에 대응하기 위하여 다양한 보안대책이 시행되고 있으나, 대부분의 보안 대책은 내 외부 사이의 경계선을 보안하는데 초점이 맞추어져 있다. 이는 외부로부터 발생하는 공격을 탐지하고 대응하기에 효과적이지만, 내부에서 발생하는 보안 사고에 취약한 실정이다. 본 연구에서는 효과적인 내부유출방지를 위해 사용자 행위정보 중 기술유출 행위에 해당하는 행위를 식별하고 기술유출 행위 탐지 항목을 설계하였다. 설계 방법으로는 선행연구 기반의 기존 기술유출 탐지 방법들을 분석하고, 기술유출 사고 사례를 기술유출 행위 관점에서 분석하여 기술유출 행위로 식별 가능한 탐지 항목들을 도출하였다. 도출한 기술유출 행위 탐지 항목은 통계적 검증을 통해 적합 타당성, 신뢰성을 모두 확보하였으며, 항목 간 상관분석을 통해 항목 간 연관 정도를 확인하였다. 본 연구의 결과물을 통하여 향후 선행연구와 유출경험 사고 사례 기반의 기술유출 시나리오 설계에 기반이 될 수 있을 것으로 기대된다.

• Nuclear Engineering and Technology
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• 제44권8호
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• pp.977-984
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• 2012

The cross-correlation technique has been widely used for leakage detection of buried pipes, and this technique can be successfully applied when the leakage signal has a high signal-to-noise ratio. In the case of a power plant, the measured leakage signals obtained from the sensors may contain background noise and mechanical noise generated by adjacent machinery. In such a case, the conventional method using the cross-correlation function may fail to estimate the leakage point. In order to enhance the leakage estimation capability of a buried pipe in a noisy environment, an improved cross-correlation technique is proposed. It uses a noise rejection technique in the frequency domain to effectively eliminate the tonal noise due to rotating machinery. Experiments were carried out to verify the validity of the proposed method. The results show that even in a tonal noisy environment, the proposed method can provide more reliable means for estimating the time delay of the leakage signals.

• 한국콘텐츠학회논문지
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• 제13권1호
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• pp.48-54
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• 2013

IT융합기술의 발전에 따라 누수탐지를 위한 인프라스트럭처가 구축되면서, 파손된 관로의 위치 및 규모의 파악 기술이 부각되고 있다. 또한 상수도 시설의 누수로 인한 수자원의 고갈 때문에 효율적으로 누수를 탐지할 수 있는 방법이 시급하다. 본 논문에서는 파워스펙트럼 분석을 이용한 누수탐지 모니터링 시뮬레이션을 제안하였다. 제안한 누수탐지 모니터링 시뮬레이션에서 반사파 파형을 측정한다. 수집된 반사파 파형으로부터 변화율을 계산한다. 그리고 고속 퓨리에 변환을 이용한 파워 스펙트럼 분석은 누수의 크기와 반사파 파형의 상관관계를 평가한다. 이를 시뮬레이션의 논리적 타당성과 유효성을 검증하기 위해 실험적인 적용을 시도하고자 한다. 따라서 실시간 누수탐지를 제공하여 효율적인 관리에 대한 만족도와 서비스의 질을 향상시켰다.

• Nuclear Engineering and Technology
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• 제56권5호
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• pp.1725-1732
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• 2024

In nuclear power plants, reactor coolant leakage can occur due to various reasons. Early detection of leaks is crucial for maintaining the safety of nuclear power plants. Currently, a detection system is being developed in Korea to identify reactor coolant system (RCS) leakage of less than 0.5 gpm. Typically, RCS leaks are detected by monitoring temperature, humidity, and radioactivity in the containment, and a water level in the sump. However, detecting small leaks proves challenging because the resulting changes in the containment humidity and temperature, and the sump water level are minimal. To address these issues and improve leak detection speed, it is necessary to quantify the leaks and develop an artificial intelligence-based leak detection system. In this study, we employed bidirectional long short-term memory, which are types of neural networks used in artificial intelligence, to predict the relative humidity in the leakage area for leak quantification. Additionally, an optimization technique was implemented to reduce learning time and enhance prediction performance. Through evaluation of the developed artificial intelligence model's prediction accuracy, we expect it to be valuable for future leak detection systems by accurately predicting the relative humidity in a leakage area.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2009년도 춘계 학술발표회
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• pp.798-804
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• 2009

Damaged liners may be detected by using leakage detection systems. For the reason, many types of leakage detection systems are applied to analyze or detect damages of lining system such as electrical detection method for the landfill sites. However, most of them can be applied in the new landfill construction sites because sensors should be installed in the bottom of liner systems. This paper shows a case study reviewing the development of a fence type leakage detection method, monitoring system and pilot plant test results, so that they can be economically and efficiently applied to actual used or in-use sites without a leakage detection system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4662-4679
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• 2015

Currently, the leakage of internal information has emerged as one of the most significant security concerns in enterprise computing environments. Especially, damage due to internal information leakage by insiders is more serious than that by outsiders because insiders have considerable knowledge of the system's identification and password (ID&P/W), the security system, and the main location of sensitive data. Therefore, many security companies are developing internal data leakage prevention techniques such as data leakage protection (DLP), digital right management (DRM), and system access control, etc. However, these techniques cannot effectively block the leakage of internal information by insiders who have a legitimate access authorization. The security system does not easily detect cases which a legitimate insider changes, deletes, and leaks data stored on the server. Therefore, we focused on the insider as the detection target to address this security weakness. In other words, we switched the detection target from objects (internal information) to subjects (insiders). We concentrated on biometrics signals change when an insider conducts abnormal behavior. When insiders attempt to leak internal information, they appear to display abnormal emotional conditions due to tension, agitation, and anxiety, etc. These conditions can be detected by the changes of biometrics signals such as pulse, temperature, and skin conductivity, etc. We carried out experiments in two ways in order to verify the effectiveness of the emotional recognition technology based on biometrics signals. We analyzed the possibility of internal information leakage detection using an emotional recognition technology based on biometrics signals through experiments.

• Nuclear Engineering and Technology
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• 제54권7호
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• pp.2748-2754
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• 2022

Because existing reactant coolant system (RCS) leakage detection mechanisms are insensitive to small leaks, a real-time, direct detection system with a detection threshold below 0.5 gpm·hr^-1 was studied. A beta-ray detection system using a silicon detector with good energy resolution for beta rays and a low gamma-ray response was proposed. The detection performance in the leakage condition was evaluated through experiments and simulations. The concentration of ¹⁶N in the coolant corresponding to a coolant leakage of 0.5 gpm was calculated using the analytic method and ORIGEN-ARP. Based on the concentration of ¹⁶N and the measurement of the silicon detector with ⁹⁰Sr/⁹⁰Y, the beta-ray count rate was estimated using MCNPX. To evaluate the effect of gamma rays inside the containment building, the signal-to-noise ratio (SNR) was calculated. To evaluate the count rate ratio, the radiation field inside the containment building was simulated using MCNPX, and response evaluation experiments were performed using beta and gamma rays on the silicon detector. The expected beta-ray count rate at 0.5 gpm leakage was 7.26 × 10⁵ counts/sec, and the signal-to-background count rate ratio exceeded 88 for a transport time of 10 s, demonstrating its suitability for operation inside a reactor containment building.

• Journal of Mechanical Science and Technology
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• 제15권2호
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• pp.232-238
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• 2001

Fast Fourier Transformation is employed to convert the head variation of a pipeline in the time domain to the amplitude of the frequency domain. Applying method of characteristics to a pipeline provides a significant frequency range for a surge introduced from the valve modulation. Inverse Fast Fourier Transformation and a Finite Impulse Response Filter can be used to remove any possible noise existing from the significant frequency range of an unsteady condition. A filtered signal shows higher potential for the inverse calculation of leakage detection than the noise-added signal does. The respective performances of Inverse Fast Fourier Transformation and a Finite Impulse Response Filter are compared in terms of leakage detection capability. Characteristics of the frequency range for multiple leakages were investigated to validate the effectiveness of the noise control method in the frequency domain.

• Nuclear Engineering and Technology
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• 제51권1호
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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.