• 한국압력기기공학회 논문집
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• 제14권2호
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• pp.41-48
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• 2018

In this study, the dynamic absorber and the damper are applied to improve the seismic performance of the piping system, and their quantitative effects on the piping system performance are examined. For this purpose, the response performances of piping system applied with the dynamic absorber/damper are compared with those of the original piping system. Firstly, the frequency response analyses of the piping system with the presence or the absence of dynamic absorber/damper are performed and these results are compared. It has been shown that the maximum acceleration response per the frequency of the piping system is considerably reduced by installing the dynamic absorber and the damper. Secondly, the seismic responses of the piping systems with and without dynamic absorber/damper are compared. As a result of the numerical analyses, it is confirmed that key responses are reduced by 17%-63% due to the installation of the dynamic absorber and damper. Finally, as a result of the seismic performance evaluation, it is confirmed that the HCLPF (High Confidence of Low Probability of Failure) seismic performances are increased by 1.22 to 2.70 times with respect to the failure modes with an aid of the dynamic absorber and damper.

• Nuclear Engineering and Technology
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• 제53권3호
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• pp.911-919
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• 2021

In this paper, the design stress intensity values for the plate-type fuel assembly for research reactor are presented. Through a tensile test, the material properties of the cladding (aluminum alloy 6061) and structural material (aluminum alloy 6061-T6), in this case the yield and ultimate tensile strengths, Young's modulus and the elongation, are measured with the temperatures. The empirical equations of the material properties with respect to the temperature are presented. The cladding undergoes several heat treatments and hardening processes during the fabrication process. Cladding strengths are reduced compared to those of the raw material during annealing. Up to a temperature of 150 ℃, the strengths of the cladding do not significantly decrease due to the dislocations generated from the cold work. However, over 150 ℃, the mechanical strengths begin to decrease, mainly due to recrystallization, dislocation recovery and precipitate growth. Taking into account the uncertainty of the 95% probability and 95% confidence level, the design stress intensities of the cladding and structural materials are established. The presented design stress intensity values become the basis of the stress design criteria for a safety analysis of plate-type fuels.

• Smart Structures and Systems
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• 제24권4호
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• pp.507-524
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• 2019

A Bayesian dynamic linear model (BDLM) is presented for a data-driven analysis for response prediction and load effect separation of a revolving auditorium structure, where the main loads are self-weight and dead loads, temperature load, and audience load. Analyses are carried out based on the long-term monitoring data for static strains on several key members of the structure. Three improvements are introduced to the ordinary regression BDLM, which are a classificatory regression term to address the temporary audience load effect, improved inference for the variance of observation noise to be updated continuously, and component discount factors for effective load effect separation. The effects of those improvements are evaluated regarding the root mean square errors, standard deviations, and 95% confidence intervals of the predictions. Bayes factors are used for evaluating the probability distributions of the predictions, which are essential to structural condition assessments, such as outlier identification and reliability analysis. The performance of the present BDLM has been successfully verified based on the simulated data and the real data obtained from the structural health monitoring system installed on the revolving structure.

• 유통과학연구
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• 제20권5호
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• pp.49-64
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• 2022

Purpose: This research aims to determine the quality of online store designs that make consumers who use online market board applications have the urge to make impulse buying. This research was conducted because impulse buying is the most common buying behavior. Research design, data and methodology: This research used non-probability sampling. The sample size was 195 respondents from the distribution and service industries by applying a purposive sampling technique. The data collection technique employed a questionnaire distributed online according to predetermined criteria: mobile device users who accessed the online market board application and made at least one purchase in the last six months. The data analysis method utilized was structural equation modeling (SEM). Results: The findings revealed that usability, functionality, and sociability factors affected hedonic and utilitarian search. Furthermore, these findings proved that hedonic search affected impulse buying drives. In contrast, the utilitarian search did not affect impulse buying drives. Conclusions: The usability, functionality, and sociability factors supported hedonic and utilitarian searches. Consumer information security increased consumer confidence in an online store because it was considered to protect matters related to their privacy. The hedonic search also increased impulse buying drives. Consumers prefer to use their spare time to search through online market board applications, which provide many attractive promos.

• Nuclear Engineering and Technology
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• 제53권4호
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• pp.1331-1344
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• 2021

This study is to evaluate the seismic capacity of the fire-damaged cabinet facility in a nuclear power plant (NPP). A prototype of an electrical cabinet is modeled using OpenSees for the numerical simulation. To capture the nonlinear behavior of the cabinet, the constitutive law of the material model under the fire environment is considered. The experimental record from the impact hammer test is extracted trough the frequency-domain decomposition (FDD) method, which is used to verify the effectiveness of the numerical model through modal assurance criteria (MAC). Assuming different temperatures, the nonlinear time history analysis is conducted using a set of fifty earthquakes and the seismic outputs are investigated by the fragility analysis. To get a threshold of intensity measure, the Monte Carlo Simulation (MCS) is adopted for uncertainty reduction purposes. Finally, a capacity estimation model has been proposed through the investigation, which will be helpful for the engineer or NPP operator to evaluate the fire-damaged cabinet strength under seismic excitation. This capacity model is presented in terms of the High Confidence of Low Probability of Failure (HCLPF) point. The results are validated by the proper judgment and can be used to analyze the influences of fire on the electrical cabinet.

• 한국기계가공학회지
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• 제20권12호
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• pp.1-7
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• 2021

The deep learning image processing technique was used to prevent accidents in lathe work caused by worker negligence. During lathe operation, when the chuck is rotated, it is very dangerous if the operator's hand is near the chuck. However, if the chuck is stopped during operation, it is not dangerous for the operator's hand to be in close proximity to the chuck for workpiece measurement, chip removal or tool change. We used YOLO (You Only Look Once), a deep learning image processing program for object detection and classification. Lathe work images such as hand, chuck rotation and chuck stop are used for learning, object detection and classification. As a result of the experiment, object detection and class classification were performed with a success probability of over 80% at a confidence score 0.5. Thus, we conclude that the artificial intelligence deep learning image processing technique can be effective in preventing incidents resulting from worker negligence in future manufacturing systems.

• 방사성폐기물학회지
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• 제21권1호
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• pp.149-164
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• 2023

As part of the safety case development for generic disposal sites in Korea, it is necessary to develop generic assessment models using various geosphere-biosphere interfaces (GBIs) and potentially exposed groups (PEGs) that reflect the natural environmental characteristics and the lifestyles of people in Korea. In this study, a unique modeling strategy was developed to systematically construct and select Korean generic biosphere assessment models. The strategy includes three process steps (combination, screening, and experts' scoring) for the biosphere system conditions. First, various conditions, such as climate, topography, GBIs, and PEGs, were combined in the biosphere system. Second, the combined calculation cases were configured into interrelation matrices to screen out some calculation cases that were highly unlikely or less significant in terms of the exposure dose. Finally, the selected calculation cases were prioritized based on expert judgment by scoring the knowledge, probability, and importance. The results of this study can be implemented in the development of biosphere assessment models for Korean generic sites. It is believed that this systematic methodology for selecting the candidate calculation cases can contribute to increasing the confidence of future site-specific biosphere assessment models.

• 시스템엔지니어링학술지
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• 제19권2호
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• pp.18-31
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• 2023

Exploring artificial intelligence and machine learning for nuclear safety has witnessed increased interest in recent years. To contribute to this area of research, a machine learning model capable of accurately predicting nuclear power plant response with minimal computational cost is proposed. To develop a robust machine learning model, the Best Estimate Plus Uncertainty (BEPU) approach was used to generate a database to train three models and select the best of the three. The BEPU analysis was performed by coupling Dakota platform with the best estimate thermal hydraulics code RELAP/SCDAPSIM/MOD 3.4. The Code Scaling Applicability and Uncertainty approach was adopted, along with Wilks' theorem to obtain a statistically representative sample that satisfies the USNRC 95/95 rule with 95% probability and 95% confidence level. The generated database was used to train three models based on Recurrent Neural Networks; specifically, Long Short-Term Memory, Gated Recurrent Unit, and a hybrid model with Long Short-Term Memory coupled to Convolutional Neural Network. In this paper, the System Engineering approach was utilized to identify requirements, stakeholders, and functional and physical architecture to develop this project and ensure success in verification and validation activities necessary to ensure the efficient development of ML meta-models capable of predicting of the nuclear power plant response.

• 대한기계학회논문집B
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• 제38권7호
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• pp.647-656
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• 2014

본 연구에서는 ISO GUM(불확도 표현 지침서)의 불확도 평가 방법을 보완하기 위해, 몬테카를로 방법(Monte Carlo Method, MCM)을 적용한 불확도 해석 프로그램을 개발하고, MCM과 GUM의 평가 결과를 비교하였다. 그 결과 다음과 같은 결과를 도출하였다. 첫째, 측정량의 확률 분포가 정규 분포가 아닌 때에도 MCM 방법은 정확한 포함 구간을 제공한다. 둘째, 정규 분포가 아닌 다른 분포들 몇몇 개가 합성되는 경우 그 확률 분포가 정규로 보이더라도 실제로는 정규가 아닌 경우가 있으며, 이의 판단은 합성 분산의 확률 분포로 할 수 있다. 셋째, 자유도가 낮은 A형 불확도가 불확도 평가에 포함된 경우 GUM은 포함 구간을 저평가하는 것을 알 수 있었고, 이러한 저평가 문제는 A형 표준 불확도에 t-분포의 표준 편차를 곱해주면 사라지는 것을 알 수 있었다. 이 경우 합성 분산의 유효 자유도는 확장 불확도 계산에 불필요하고, 신뢰의 수준 95 %의 포함 인자는 1.96이 적정한 것을 알 수 있었다.

• 기술사
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• 제20권3호
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• pp.15-25
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• 1987

Statistical control charts are useful tools to monitor and control the manufacturing processes and are widely used in most Korean industries. Many Korean companies, however, do not always obtain desired results from the traditional control charts by Shewhart such as the X-chart, X-chart, X-chart, etc. This is partly because the quality charterstics of the process are not distributed normally but are skewed due to the intermittent production, small lot size, etc. In Shewhart X-chart, which is the most widely used one in Korea, such skewed distributions make the plots to be inclined below or above the central line or outside the control limits although no assignable causes can be found. To overcome such shortcomings in nonnormally distributed processes, a distribution-free type of confidence interval can be used, which should be based on order statistics. This thesis is concerned with the design of control chart based on a sample median which is easy to use in practical situation and therefore properties for nonnormal distributions may be easily analyzed. Control limits and central lines are given for tile more famous nonnormal distributions, such as Gamma, Beta, Lognormal, Weibull, Pareto, Truncated-normal distributions. Robustness of the proposed median control chart is compared with that of the X-chart, the former tends to be superior to the latter as the probability distribution of the process becomes more skewed. The average run length to detect the assignable cause is also compared when the process has a Normal or a Gamma distribution for which the properties of X are easy to verify, the proposed chart is slightly worse than the X-chart for the normally distributed product but much better for Gamma-distributed products. Average Run Lengths of the other distributions are also computed. To use the proposed control chart, the probability distribution of the process should be known or estimated. If it is not possible, the results of comparison of the robustness force us to use the proposed median control chart based on a normal distribution. To estimate the distribution of the process, Sturge's formula is used to graph the histogram and the method of probability plotting, $X^2$-goodness of fit test and Kolmogorov-Smirnov test, are discussed with real case examples. A comparison of the propose4 median chart and the X chart was also performed with these examples and the median chart turned out to be superior to the X-chart.