• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_1
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• pp.493-504
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• 2022

Recently, as interest in eco-friendliness grows, the supply of hybrid electric vehicles and pure electric vehicles (EVs) for improving fuel efficiency of automobiles is rapidly expanding. The average daily energy consumption of electric vehicles is less than 20 [%] of the total ESS capacity of the vehicle, and research on additional functions using the ESS of the vehicle is urgently needed to expand the supply of electric vehicles. V2H(Vehicle to Home), like V2G(Vehicle to Grid), includes the concept of cooperating with system stabilization using ESS of electric vehicles. In addition, it includes various operations that can realize home welfare, such as uninterrupted power supply in case of power outage at home, and power supply for home DC devices. Therefore, in order to expand the supply of eco-friendly electric vehicles, it is urgently required to develop a V2H system with various functions that can realize home welfare. In this paper, we propose a V2H system with a CLLC resonant converter and a non-isolated step-up converter that can solve different impedance and resonant frequencies depending on the power transfer direction. The proposed V2H system is 6 [kVA] applicable to 150-450 [V], the voltage range that can use the ESS voltage for electric vehicles, and is designed with a capacity that can handle instantaneous electricity use at home. In addition, in order to verify the feasibility, an experiment by Psim simulation and prototype production was performed.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.212-212
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• 2023

비점오염원관리와 같이 장기적인 유역 관리 계획에서 유역 내 오염원 평가는 정말 중요하다. 유역 내 오염원 평가는 강우 유출에 의한 비점오염 발생원이 어디서 얼마나 발생시키는지에 대한 정량적인 조사가 필요하다. 유역 내의 오염원에 대한 정량적인 조사는 많은 비용과 시간이 필요하다. 이러한 비용과 시간을 줄이기 위해 유역단위 수리 수문 모델을 사용하고 있다. 유역단위 수리수문 모델은 HSPF (Hydrological Simulation Program in Fortran), SWAT (Soil and Water Assessment Tool), L-THIA ACN-WQ(The Long-term Hydrologic Impact Assessment Model with Asymptotic Curve Number Regression Equation and Water Quality model)등 다양한 모델이 사용되고 있다. 하지만 유역 모델을 통한 모의는 다양한 연산 과정을 진행하여 모의까지 많은 시간이 필요하다는 단점이 있다. 이에 따라 데이터 기반 모델링 기법(머신러닝/딥러닝)을 이용한 유출 및 수질 예측 연구가 많이 이루어지고 있다. 단순 머신러닝/딥러닝 기반 모델링 기법은 점(최종유출구)에서의 예측만 가능하여 최적관리 기법 적용 등과 같은 유역관리 방안을 적용하기 힘들다는 문제점이 있다. 따라서 본 연구에서 머신러닝/딥러닝을 통해 일부 수문 프로세스를 대체하고 소유역별 하도추적 기법을 연계하여 유량 및 수질 항목들의 모의가 가능한 하이브리드 모델을 개발하였다. 이는 머신러닝/딥러닝이 유역 모델의 일부 연산 과정을 대체하여 모의시간이 빠르며, 기존 머신러닝/딥러닝 예측 모델에서 평가가 어려웠던 유역 관리 방안 및 최적관리기법 적용 평가에도 활용이 가능할 것으로 판단이 된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.273-273
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• 2022

혼합층(Mixed layer)은 온도가 일정한 수심층으로, 해수표면에 작용하는 바람의 영향으로 인하여 해수가 위아래로 섞여 형성된다. 이러한 혼합층은 영양염의 순환과 산소의 공급 등과 함께 일차생산량을 결정하는 중요한 요인이 될 수 있으며 혼합층 두께의 변동은 양식 산업에 영향을 미칠 수 있다. 최근에는 기후변화로 인한 해수면 상승 및 해수온 상승 등이 지속되고 있으며, 이러한 현상은 해양생태계의 변화를 초래하여 수산업의 피해를 유발할 수 있다(강원연구원, 2017). 이에 국립수산과학원, 기상청, 국립해양조사원 등 유관기관에서는 정선해양 수온 관측 및 해수순환모델을 이용하여 혼합층의 분석을 수행하고 있으나 격자 구축 및 초기·경계장 설정의 한계가 존재하여 정밀하고 정확한 혼합층 분석에는 어려움이 있다. 이에 본 연구에서는 비정형격자를 사용하여 격자 구축에 제약이 없는 SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model)을 이용하여 우리나라 연안해역의 계절변화 및 기후변동성에 따른 혼합층 두께의 변화를 검토하고자 한다. 연구대상지는 서해·동해·남해를 포함한 우리나라 전체 연안 해역(위도: 32°N ~ 39°N, 경도: 124°E ~ 132°E)으로 선정하였으며, 격자크기 100 ~ 3,000 m인 삼각격자로 격자를 구축하였다. 혼합층을 분석하기 위하여 수직격자 층은 50층으로 SZ(Sigma Z coordinate system)좌표계를 사용하였다. 초기·경계장은 FES(Finite Element Solution)2014, HYCOM(Hybrid Coordinate Ocean Model) 및 대기모델 결과를 이용하여 설정하였다. 수치모형 검증을 위하여 수온관측소에서 수심별 측정한 수온 값과 SCHISM 결과 값을 비교하였고, 상대오차가 약 10% 이내로 나타나 모형의 정확도를 확인하였다. 최종적으로 해수면 상승 및 해수온 상승 시나리오를 고려하여 계절별 연안해역의 혼합층 두께의 변화 양상에 대하여 검토하였다. 향후에는 보다 정밀한 대기모델과의 혼합모형 구축 및 다양한 수심 별 관측자료를 활용한다면 실무에서 적용 가능한 혼합층 분석 및 수산업 피해 발생 지역에 대한 피해저감 대책 수립이 가능할 것으로 판단된다.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.51-61
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• 2006

An efficient and accurate hybrid reliability analysis method is proposed in this paper to quantify the risk of an axially loaded single pile considering pile-soil interaction behavior and uncertainties in various design variables. The proposed method intelligently integrates the concepts of the response surface method, the finite difference method, the first-order reliability method, and the iterative linear interpolation scheme. The load transfer method is incorporated into the finite difference method for the deterministic analysis of a single pile-soil system. The uncertainties associated with load conditions, material and section properties of a pile and soil properties are explicitly considered. The risk corresponding to both serviceability limit state and strength limit state of the pile and soil is estimated. Applicability, accuracy and efficiency of the proposed method in the safety assessment of a realistic pile-soil system subjected to axial loads are verified by comparing it with the results of the Monte Carlo simulation technique.

• Structural Engineering and Mechanics
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• v.81 no.1
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• pp.11-28
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• 2022

This paper considers the combination of cyclic and axial loads to investigate the hysteretic performance of H-section 6061-T6 aluminum alloy members. The hysteretic performance of aluminum alloy members is the basis for the seismic performance of aluminum alloy structures. Despite the prevalence of aluminum alloy reticulated shells structures worldwide, research into the seismic performance of aluminum alloy structures remains inadequate. To address this deficiency, we design and conduct cyclic axial load testing of three H-section members based on a reliable testing system. The influence of slenderness ratios and bending direction on the failure form, bearing capacity, and stiffness degradation of each member are analyzed. The experiment results show that overall buckling dominates the failure mechanism of all test members before local buckling occurs. As the load increases after overall buckling, the plasticity of the member develops, finally leading to local buckling and fracture failure. The results illustrate that the plasticity development of the local buckling position is the main reason for the stiffness degradation and failure of the member. Additionally, with the increase of the slenderness ratio, the energy-dissipation capacity and stiffness of the member decrease significantly. Simultaneously, a finite element model based on the Chaboche hybrid strengthening model is established according to the experiment, and the rationality of the constitutive model and validity of the finite element simulation method are verified. The parameter analysis of twenty-four members with different sections, slenderness ratios, bending directions, and boundary conditions are also carried out. Results show that the section size and boundary condition of the member have a significant influence on stiffness degradation and energy dissipation capacity. Based on the above, the appropriate material constitutive relationship and analysis method of H-section aluminum alloy members under cyclic loading are determined, providing a reference for the seismic design of aluminum alloy structures.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.713-722
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• 2022

In this paper, the flow performance and aero-acoustic noise generated by the target centrifugal fan system were investigated numerically and experimentally. Also, the numerical method for Computational Aero-Acoustics were evaluated by comparing each method. To analyze the performance of the centrifugal fan experimentally, the acoustic power level was measured in the semi-anechoic chamber using microphones, and the active frequency range for the noise performance was identified and that frequency range was applied for Computational Aero-Acoustics (CAA) techniques as sampling frequency. Then, Navier-Stokes equation and the Ffowcs Williams&Hawking equations were used to analyze the flow and sound power numerically, respectively, and a virtual acoustic radiation plane was designed and used for the implementation of the sound field. The accuracy and numerical characteristics of the numerical methods were validated by comparing simulated acoustic power levels with acoustic power levels measured.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.139-145
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• 2023

These days, protecting location privacy has become essential and really challenging, especially protecting it from smart applications and services that rely on Location-Based Services (LBS). As the technology and the services that are based on it are developed, the capability and the experience of the attackers are increased. Therefore, the traditional protection ways cannot be enough and are unable to fully ensure and preserve privacy. Previously, a hybrid approach to privacy has been introduced. It used an obfuscation technique, called Double-Obfuscation Approach (DOA), to improve the privacy level. However, this approach has some weaknesses. The most important ones are the fog nodes that have been overloaded due to the number of communications. It is also unable to prevent the Tracking and Identification attacks in the Mix-Zone technique. For these reasons, this paper introduces a developed and enhanced approach, called Multi-Obfuscation Approach (MOA that mainly depends on the communication between neighboring fog nodes to overcome the drawbacks of the previous approach. As a result, this will increase the resistance to new kinds of attacks and enhance processing. Meanwhile, this approach will increase the level of the users' privacy and their locations protection. To do so, a big enough memory is needed on the users' sides, which already is available these days on their devices. The simulation and the comparison prove that the new approach (MOA) exceeds the DOA in many Standards for privacy protection approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1873-1893
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• 2023

The development of lightweight, low energy and small-sized sensors incorporated with the wireless networks has brought about a phenomenal growth of Wireless Sensor Networks (WSNs) in its different fields of applications. Moreover, the routing of data is crucial in a wide number of critical applications that includes ecosystem monitoring, military and disaster management. However, the time-delay, energy imbalance and minimized network lifetime are considered as the key problems faced during the process of data transmission. Furthermore, only when the functionality of cluster head selection is available in WSNs, it is possible to improve energy and network lifetime. Besides that, the task of cluster head selection is regarded as an NP-hard optimization problem that can be effectively modelled using hybrid metaheuristic approaches. Due to this reason, an Improved Coyote Optimization Algorithm-based Clustering Technique (ICOACT) is proposed for extending the lifetime for making efficient choices for cluster heads while maintaining a consistent balance between exploitation and exploration. The issue of premature convergence and its tendency of being trapped into the local optima in the Improved Coyote Optimization Algorithm (ICOA) through the selection of center solution is used for replacing the best solution in the search space during the clustering functionality. The simulation results of the proposed ICOACT confirmed its efficiency by increasing the number of alive nodes, the total number of clusters formed with the least amount of end-to-end delay and mean packet loss rate.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.479-485
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• 2023

Although fire incidents occur frequently in factory buildings, the focus has primarily been on property damage rather than human casualties. In this study, we conducted an analysis of RSET(Required Safe Egress Time) variation by examining the relocation of workbenchs using evacuation simulations. The results demonstrated that a simple change in workbench placement led to different RSET and variations in the feasibility of evacuation. Specifically, arranging workbenchs in a vertical configuration reduced travel time for workers and minimized total evacuation time. The hybrid layout of "vertical-horizontal" exhibited the shortest RSET, while the "horizontal-vertical" configuration resulted in the longest RSET. These research findings are significant as they provide practical alternatives to decrease RSET in small-scale factories where additional investments beyond essential safety equipment may pose challenges due to budget constraints. However, it is important to note that this study solely focused on comparing RSET while controlling for all other factors, without considering real-life fire simulations. Therefore, further research is necessary to integrate fire simulations and conduct comprehensive assessments of evacuation safety.