• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.3985-3995
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• 2022

The emergence of new nanoscale technologies has imposed significant challenges to designing reliable electronic systems in radiation environments. A few types of radiation like Total Ionizing Dose (TID) can cause permanent damages on such nanoscale electronic devices, and current state-of-the-art technologies to tackle TID make use of expensive radiation-hardened devices. This paper focuses on a novel and different approach: using machine learning algorithms on consumer electronic level Field Programmable Gate Arrays (FPGAs) to tackle TID effects and monitor them to replace before they stop working. This condition has a research challenge to anticipate when the board results in a total failure due to TID effects. We observed internal measurements of FPGA boards under gamma radiation and used three different anomaly detection machine learning (ML) algorithms to detect anomalies in the sensor measurements in a gamma-radiated environment. The statistical results show a highly significant relationship between the gamma radiation exposure levels and the board measurements. Moreover, our anomaly detection results have shown that a One-Class SVM with Radial Basis Function Kernel has an average recall score of 0.95. Also, all anomalies can be detected before the boards are entirely inoperative, i.e. voltages drop to zero and confirmed with a sanity check.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4412-4421
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• 2022

The pressure measurement in the high-temperature liquid metal system, such as Sodium-cooled Fast Reactor(SFR), is important and yet it is very challenging due to its nature. The measuring pressure is relatively at low range and the applied temperature varies in wide range. Moreover, the pressure transfer material in impulse line needs to considered the high temperature condition. The conventional diaphragm-based approach cannot be used for it is impossible to remove the effect of thermal expansion. In this paper, the Fiber Bragg Grating(FBG) sensor-based pressure measuring concept is suggested that it is free of problems induced by the thermal expansion. To verify this concept, a prototype was fabricated and tested in an appropriate conditions. The uncertainty analysis result of the experiment is also included. The final result of this study clearly showed that the FBG-based pressure transmitter system is applicable to the extreme environment, such as SFR and any other high-temperature liquid metal system and the measurement uncertainty is within reasonable range.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.475-483
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• 2023

The high-flux advanced neutron application reactor (HANARO) is a multi-purpose research reactor at the Korea Atomic Energy Research Institute (KAERI). HANARO has been used in scientific and industrial research and developments. Therefore, stable operation is necessary for national science and industrial prospects. This study proposed an anomaly detection system based on deep learning, that supports the stable operation of HANARO. The proposed system collects multiple sensor data, displays system information, analyzes status, and performs anomaly detection using deep autoencoder. The system comprises communication, visualization, and anomaly-detection modules, and the prototype system is implemented on site in 2021. Finally, an analysis of the historical data and synthetic anomalies was conducted to verify the overall system; simulation results based on the historical data show that 12 cases out of 19 abnormal events can be detected in advance or on time by the deep learning AD model.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.603-622
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• 2023

Human error (HE) is an important concern in safety-critical systems such as nuclear power plants (NPPs). HE has played a role in many accidents and outage incidents in NPPs. Despite the increased automation in NPPs, HE remains unavoidable. Hence, the need for HE detection is as important as HE prevention efforts. In NPPs, HE is rather rare. Hence, anomaly detection, a widely used machine learning technique for detecting rare anomalous instances, can be repurposed to detect potential HE. In this study, we develop an unsupervised anomaly detection technique based on generative adversarial networks (GANs) to detect anomalies in manually collected surveillance data in NPPs. More specifically, our GAN is trained to detect mismatches between automatically recorded sensor data and manually collected surveillance data, and hence, identify anomalous instances that can be attributed to HE. We test our GAN on both a real-world dataset and an external dataset obtained from a testbed, and we benchmark our results against state-of-the-art unsupervised anomaly detection algorithms, including one-class support vector machine and isolation forest. Our results show that the proposed GAN provides improved anomaly detection performance. Our study is promising for the future development of artificial intelligence based HE detection systems.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2195-2205
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• 2023

One of the salient nuclear fuel performance parameters for new fuel types under development is changes in fuel thickness. To test the new commercially fabricated U-10Mo monolithic plate-type fuel, an irradiation experiment was designed that consisted of multiple mini-plate capsules distributed within the Advanced Test Reactor (ATR) core, the mini-plate 1 (MP-1) experiment. Each capsule contains eight mini-plates that were either fueled or "dummy" plates. Fuel thickness changes within a fuel assembly can be characterized by measuring the gaps between the plates ultrasonically. The channel gap probe (CGP) system is designed to measure the gaps between the plates and will provide information that supports qualification of U-10Mo monolithic fuel. This study will discuss the design and the results from the use of a custom-designed CGP system for characterizing the gaps between mini-plates within the MP-1 capsules. To ensure accurate and repeatable data, acceptance and calibration procedures have been developed. Unfortunately, there is no "gold" standard measurement to compare to CGP measurements. An effort was made to use plate thickness obtained from post-irradiation measurements to derive channel gap estimates for comparison with the CGP characterization.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2642-2649
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• 2023

A real-time unmeasured dynamic response prediction process for the nuclear power plant pressure pipeline is proposed and its performance is tested in the test-loop system (KAERI). The aim of the process is to predict unmeasurable or unreachable dynamic responses such as acceleration, velocity, and displacement by using a limited amount of directly measured physical responses. It is achieved by combining a well-constructed finite element model and robust inverse force identification algorithm. The pressure pipeline system is described by using the displacement-pressure vibro-acoustic formulation to consider fully filled liquid effect inside the pipeline structure. A robust multiphysics modal projection technique is employed for the real-time sensor synchronized prediction. The inverse force identification method is also derived and employed by using Bathe's time integration method to identify the full-field responses of the target system from the modal domain computation. To validate the performance of the proposed process, an experimental test is extensively performed on the nuclear power plant pressure pipeline test-loop under operation conditions. The results show that the proposed identification process could well estimate the unmeasured acceleration in both frequency and time domain faster than 32,768 samples per sec.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1431-1440
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• 2024

The study aimed to develop a laser-based distance meter (LDM) to improve water surface identification for clinical MeV electron beam dosimetry, as inaccurate water surface determination can lead to imprecise positioning of ionization chambers (ICs). The LDM consisted of a laser ranging sensor, a signal processing microcontroller, and a tablet PC for data acquisition. I₅₀ (the water depth at which ionization current drops to 50 % of its maximum) measurements of electron beams were performed using six different types of ICs and compared to other water surface identification methods. The LDM demonstrated reproducible I₅₀ measurements with a level of 0.01 cm for all six ICs. The uncertainty of water depth was evaluated at 0.008 cm with the LDM. The LDM also exposed discrepancies between I₅₀ measurements using different ICs, which was partially reduced by applying an optimum shift of IC's point of measurement (POM) or effective point of measurement (EPOM). However, residual discrepancies due to the energy dependency of the cylindrical chamber's EPOM caused remained. The LDM offers straightforward and efficient means for precision water surface identification, minimizing reliance on individual operator skills.

• Journal of Sensor Science and Technology
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• v.33 no.4
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• pp.203-208
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• 2024

Every year, approximately 350 million tons of plastic waste are generated worldwide. This waste, can degrade into microplastics, owing to factors such as temperature changes and UV exposure. These smaller plastic particles are increasingly entering the food chain through marine life, thereby raising concerns about their impact on human health. Consequently, there is an increasing need to measure microplastics. Common methods involve direct collection by using a manta trawl equipped with a 330 ㎛ mesh net or performing spectroscopic and thermal analyses on collected samples. However, these methods require complex pre-processing, which risk sample destruction. In this study, we developed a system to directly sample microplastics in aquatic environments by using laser-induced fluorescence spectroscopy. Through an analysis of the fluorescence spectra as well as, the with gradient and integration at specific points, we successfully distinguished microplastics of 100, 200, 300, and 500 ㎛ in size, and we also differentiated between polyethylene (PE) and polystyrene (PS) types.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2190-2194
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• 2024

The study investigates the dose-dependent direct X-ray sensing characteristics of Brucinium benzilate (BB) and N-acetylglycine (NAG) organic crystals. BB and NAG were prepared as a slurry and deposited as a thick film on a patterned metal electrode. The X-ray induced photocurrent response was examined for various exposure doses using an intraoral pulsed 70 keV X-ray machine connected to a source meter. Subsequently, the morphological properties and thickness of the thick films were analyzed using scanning electron microscopy (SEM). At a photon energy of 70 keV, the attenuation coefficient values for NAG and BB crystals were determined to be approximately 0.181 and 0.178 cm²/g, respectively. The X-ray stopping power of the crystals was measured using a suniray-2 X-ray imaging system. To evaluate the responsiveness of the sensors, the photocurrent sensitivity and noise equivalent dose rate (NED) were calculated for both thick films. The findings demonstrated a noteworthy capability of sensing low doses (mGy), thereby suggesting the potential application of these organic materials in X-ray sensor development.

• The Journal of Engineering Geology
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• v.3 no.3
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• pp.279-293
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• 1993

In recent yeaes, the collapses of man made structures have been encountered from time to time due to the deformation of the ground in korea. Furthermore, the possibilities of casasters from the ground deformation suCh as landslide and active fault are atrracting our attention to the deformation monitoring. In this study, two-coordinate tilt which was monitored during six months in order to develop tediniques for prevention of disasters from the ground deformation. The two-coordinate tilt which was detected by a tilt-sensor installed in shallow depth on the slope with the sensitivity of 0.0001 arc.sec in every 10 minutes was recorded continously to PC through the interface with 200-m line coonection. The observed digital tilt data. together with the relevant meteorological data were analyzed in reference to engineering application. During the whole observation period of six months, the net tilt is 10.06 arc.sec to the west and 73.88 arc.sec to the south. Consequently the ground has a tilt of 74.56 arc.sec to the direction of $S7.75^{\circ}W$ with average tilting of 0.02 arc.sec/hour. In spite of such fast and large tilting, it is interpreted in view of engineering aspects that the site is much safe from danger, since both East-West and North-South components of tilt converge as time goes by. Two categories of deformational events are recognized ; one is toward the direction of surface slope and the other is to the direction of increased pore pressure. Tiks are acenain to have a close relation with precipitation of rain. The daily variation of two-coordinate tilt is delayed 4.3 hours in average after the variation of atmospheric temperature. A certain correlation between atmospheric pressure and deformation might be revealed.