• Nuclear Engineering and Technology
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• v.52 no.6
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• pp.1318-1326
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• 2020

Structural modification in the electrical cabinet is investigated by a proposed procedure that comprises of an experimental, analytical and numerical solution. This research emphasizes the linear dynamic analysis of the cabinet that is studied under the seismic excitation to demonstrate the real behavior of the cabinets in NPP. To this end, an actual electric cabinet is experimentally tested using an impact hammer test which reveals the fundamental parameters of the cabinet. The Frequency-domain decomposition (FDD) method is used to extract the dynamic properties of the cabinet from the experiment which is then used for numerical modeling. To validate the dynamic properties of the cabinet an analytical solution is suggested. The calibrated model is analyzed under the floor response obtained from the Connecticut nuclear power plant structure excited by Tabas 1978 (Mw 7.4) earthquake. Eventually, the grouping effect of the cabinets is proposed which represents the influence on the dynamic modification. This grouping of the cabinets is described more sophisticatedly by the theoretical understating, which results in a significant change in the seismic response. Considering the grouping effects will be helpful in the assessment of the real seismic behavior, design, and performance of cabinets.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1199-1209
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• 2021

The detection of unexpected loose parts in the primary coolant system in a nuclear power plant remains an extremely important issue. It is essential to develop a methodology for the localization and mass estimation of loose parts owing to the high prediction error of conventional methods. An effective approach is presented for the localization and mass estimation of a loose part using machine-learning and deep-learning algorithms. First, a methodology was developed to estimate both the impact location and the mass of a loose part at the same times in a real structure in which geometric changes exist. Second, an impact database was constructed through a series of impact finite-element analyses (FEAs). Then, impact parameter prediction modes were generated for localization and mass estimation of a simulated metallic loose part using machine-learning algorithms (artificial neural network, Gaussian process, and support vector machine) and a deep-learning algorithm (convolutional neural network). The usefulness of the methodology was validated through blind tests, and the noise effect of the training data was also investigated. The high performance obtained in this study shows that the proposed methodology using an FEA-based database and deep learning is useful for localization and mass estimation of loose parts on site.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.3944-3951
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• 2021

Several reasons such as no free lunch theorem indicate that there is not a universal Feature selection (FS) technique that outperforms other ones. Moreover, some approaches such as using synthetic dataset, in presence of large number of FS techniques, are very tedious and time consuming task. In this study to tackle the issue of dependency of estimation accuracy on the selected FS technique, a methodology based on the heterogeneous ensemble is proposed. The performance of the major learning algorithms of neural network (i.e. the FFNN-BR, the FFNN-LM) in combination with the diverse FS techniques (i.e. the NCA, the F-test, the Kendall's tau, the Pearson, the Spearman, and the Relief) and different combination techniques of the heterogeneous ensemble (i.e. the Min, the Median, the Arithmetic mean, and the Geometric mean) are considered. The target parameters/transients of Bushehr nuclear power plant (BNPP) are examined as the case study. The results show that the Min combination technique gives the more accurate estimation. Therefore, if the number of FS techniques is m and the number of learning algorithms is n, by the heterogeneous ensemble, the search space for acceptable estimation of the target parameters may be reduced from n × m to n × 1. The proposed methodology gives a simple and practical approach for more reliable and more accurate estimation of the target parameters compared to the methods such as the use of synthetic dataset or trial and error methods.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4679-4683
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• 2022

Environmental radiation monitoring is required to protect from the effects of radiation in industrial fields such as nuclear power plant (NPP) monitoring, and various gamma camera systems are being developed. The purpose of this study is to optimize parameters of a diverging collimator composed of pure tungsten for compactness and lightness through Monte Carlo simulation. We conducted the performance evaluation based on spatial resolution and signal-to-noise ratio for point source and obtained gamma images and profiles. As a result, optimization was determined at a collimator height of 60.0 mm, a hole size of 1.5 mm, and a septal thickness of 1.0 mm. Also, the full-width-at-half-maximum was 3.5 mm and the signal-to-noise ratio was 53.5. This study proposes a compact 45° diverging collimator structure that can quickly and accurately identify the location of the source for radiation monitoring.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.568-574
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• 2024

The development of radiation-tolerant radio-frequency (RF) systems can be a solution for applications in extreme radiation environments, such as nuclear power plant monitoring and space exploration. Among the crucial components within an RF system, the low noise amplifier (LNA) stands out due to its vulnerability to TID effects, mainly relying on transistors as its main devices. In this study, the TID effects in the LNA using standard 0.18 ㎛ complementary metal oxide semiconductors (CMOS) technology are estimated and analyzed. The results show that the LNA can withstand absorbed radiation up to 100 kGy. The S₂₁, S₁₁, noise figure (NF), stability (K), and linearity of the third input intercept point (IIP3) slightly shifted from the initial values of 0.8312 dB, 0.793 dB, 0.00381 dB, 1.34406, and 2.36066 dBm, respectively which are still comparable to the typical performances. Moreover, the standard 0.18 ㎛ technology has demonstrated its radiation tolerance, as it exhibits negligible performance degradation in the conventional LNA even when exposed to radiation levels up to 100 kGy. In this context, simulation approach offers a means to predict the TID effects and estimate the radiation exposure limit for electronic devices, particularly when transistors are used as the primary RF components.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.56-63
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• 2024

In high radiation fields, gamma cameras suffer from pulse pile-up, resulting in poor energy resolution, count losses, and image distortion. To overcome this problem, various methods have been introduced to reduce the size of the aperture or pixel, reject the pile-up events, and correct the pile-up events, but these technologies have limitations in terms of mechanical design and real-time processing. The purpose of this study is to develop a real-time gamma camera to evaluate the radioactive contamination in high radiation fields. The gamma camera is composed of a pinhole collimator, NaI(Tl) scintillator, position sensitive photomultiplier (PSPMT), signal processing board, and data acquisition (DAQ). The pulse pile-up is corrected in real-time with a field programmable gate array (FPGA) using the start time correction (STC) method. The STC method corrects the amplitude of the pile-up event by correcting the time at the start point of the pile-up event. The performance of the gamma camera was evaluated using a high dose rate ¹³⁷Cs source. For pulse pile-up ratios (PPRs) of 0.45 and 0.30, the energy resolution improved by 61.5 and 20.3%, respectively. In addition, the image artifacts in the ¹³⁷Cs radioisotope image due to pile-up were reduced.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.5
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• pp.383-392
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• 2007

In this paper, we study the prediction of depth and width of a defect in steam generator tube in nuclear power plant using neural network. To this end, we first generate eddy current testing (ECT) signals for 4 defect patterns of SG tube: I-In type, I-Out type, V-In type, and V-Out type. In particular, we generate 400 ECT signals for various widths and depths for each defect type by the numerical analysis program based on finite element modeling. From those generated ECT signals, we extract new feature vectors for the prediction of defect size, which include the angle between the two points where the maximum impedance and half the maximum impedance are achieved. Using the extracted feature vector, multi-layer perceptron with one hidden layer is used to predict the size of defects. Through the computer simulation study, it is shown that the proposed method achieves decent prediction performance in terms of maximum error and mean absolute percentage error (MAPE).

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.1-10
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• 2023

The nuclear power plant(NPP)'s Instrumentation and Control(I&C) system periodically conducts integrity checks for the maintenance of self-diagnostic function during normal operation. Additionally, it performs functionality and performance checks during planned preventive maintenance periods. However, there is a need for technological development to diagnose failures and prevent accidents in advance. In this paper, we studied methods for estimating the reliability function by utilizing environmental data and self-diagnostic data of the I&C equipment. To obtain failure data, we assumed probability distributions for component features of the I&C equipment and generated virtual failure data. Using this failure data, we estimated the reliability function using representative artificial intelligence(AI) models used in survival analysis(DeepSurve, DeepHit). And we also estimated the reliability function through the Cox regression model of the traditional semi-parametric method. We confirmed the feasibility through the residual lifetime calculations based on environmental and diagnostic data.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.305-309
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• 2007

FTL(Fuel Test Loop) is a facility that confirms performance of nuclear fuel at a similar irradiation condition with that of nuclear power plant. FTL construction work began on August, 2006 and ended on March, 2007. During Construction, ensuring the worker's safety was the top priority and installation of the FTL without hampering the integrity of the HANARO was the next one. The installation works were done successfully overcoming the difficulties such as on the limited space, on the radiation hazard inside the reactor pool, and finally on the shortening of the shut down period of the HANARO. The Commissioning of the FTL is to check the function and the performance of the equipment and the overall system as well. The FTL shall start operation with high burn up test fuels in early 2008 if the commissioning and licensing progress on schedule.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.1974-1987
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• 2023

The load-following operation of small modular reactors (SMRs) requires accurate prediction of transient behaviors that can occur in the balance of plants (BOP) and the nuclear steam supply system (NSSS). However, 1-D thermal-hydraulics analysis codes developed for safety and performance analysis have conventionally excluded the BOP from the simulation by assuming ideal boundary conditions for the main steam and feed water (MS/FW) systems, i.e., an open loop. In this study, we introduced a lumped model of BOP fluid system and coupled it with NSSS without any ideal boundary conditions, i.e., in a closed loop. Various methods for coupling boundary conditions at MS/FW were tested to validate their combination in terms of minimizing numerical instability, which mainly arises from the coupled boundaries. The method exhibiting the best performance was selected and applied to a transient simulation of an integrated NSSS and BOP system of a SMART. For a transient event with core power change of 100-20-100%, the simulation exhibited numerical stability throughout the system without any significant perturbation of thermal-hydraulic parameters. Thus, the introduced boundary-condition coupling method and BOP fluid system model can expectedly be employed for the transient simulation and performance analysis of SMRs requiring daily load-following operations.