• 한국태양에너지학회 논문집
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• 제31권4호
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• pp.128-135
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• 2011

일반적으로 PEM 연료전지에서는 수분 균형이 시스템의 효율에 결정적으로 영향을 미치기 때문에, 이에 대한 균형(balance)을 잡는 것이 매우 중요하다. 특히, 촉매 층에서 물이 넘치는 익수현상(flooding)이나 건조현상(drying)이 발생하게 되면 연료전지의 효율이 급격하게 저하하므로, 항상 수분의 균형이 잡히도록 시스템을 제어하는 것이 일반적이다. 이 때,수분의 익수현상이나 건조현상은 PEM 연료전지의 용량과 주위의 환경, 즉 온도와 습도에 많은 영향을 받게 된다. 금번 논문에서는 가정용 규모인 3kW급에서 10kW급까지의 PEM 연료전지를 설치하였을 때, 주위의 환경(온도와 습도)이 수분 이동에 어떠한 영향을 미치는 지를 시간에 따라서 시뮬레이션(simulation)한 결과를 보여주고 있다. 결과에서 유입공기의 온도가 $50^{\circ}C$ 이하일 경우, 고정부하가 5kW급 이하이면 대부분이 건조현상이 발생하였으나, 고정부하가 6kW급 이상이 되면 익수현상이 운전시간이 20분 이내에서 발생하였다. 또한 고정부하를 최고 10kW급까지 올린 경우, 유입공기의 온도가 $50^{\circ}C$까지는 익수현상이 발생하였으나 $60^{\circ}C$ 이상인 경우에는 거의 건조현상이 발생함을 알 수 있었다.

• Nuclear Engineering and Technology
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• 제53권10호
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• pp.3275-3285
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• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• Journal of Power Electronics
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• 제19권3호
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• pp.702-713
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• 2019

Multilevel Inverters (MLIs) are widely used in medium voltage applications due to their various advantages. In addition, there are numerous types of MLIs for such applications. However, the diode-less 3-level (3L) T-type Neutral Point Clamped (NPC) MLI is the most advantageous due to its low conduction losses and high potential efficiency. The power circuit of a 3L T-type NPC is derived by the conventional two level inverter by a slight modification. In order to explore the MLI performance for various Pulse Width Modulation (PWM) schemes, this paper examines the operation of a 3L (five level line to line) T-type NPC MLI for various types of Multi-Carriers Pulse Width Modulation (MCPWM) schemes. These PWM schemes are compared in terms of their voltage profile, total harmonic distortion (THD) and conduction losses. In addition, a 3L T-type NPC MLI is also compared with the conventional NPC in terms of number of switches, clamping diodes, main diodes and capacitors. Moreover, the capacitor-balancing problem is also investigated using the Neutral Point Fluctuation (NPF) method with all of the MCPWM schemes. A 1kW 3L T-type NPC MLI is simulated in MATLAB/Simulink and implemented experimentally and its performance is tested with a 1HP induction motor. The results indicate that the 3L T-type NPC MLI has better performance than conventional NPC MLIs.

• Nutrition Research and Practice
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• 제15권1호
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• pp.95-105
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• 2021

BACKGROUND/OBJECTIVES: The measurement of body composition, including muscle and fat mass, remains challenging in large epidemiological studies due to time constraint and cost when using accurate modalities. Therefore, this study aimed to develop and validate prediction equations according to sex to measure lean body mass (LBM), appendicular skeletal muscle mass (ASM), and body fat mass (BFM) using anthropometric measurement, serum creatinine level, and lifestyle factors as independent variables and dual-energy X-ray absorptiometry as the reference method. SUBJECTS/METHODS: A sample of the Korean general adult population (men: 7,599; women: 10,009) from the Korean National Health and Nutrition Examination Survey 2008-2011 was included in this study. The participants were divided into the derivation and validation groups via a random number generator (with a ratio of 70:30). The prediction equations were developed using a series of multivariable linear regressions and validated using the Bland-Altman plot and intraclass correlation coefficient (ICC). RESULTS: The initial and practical equations that included age, height, weight, and waist circumference had a different predictive ability for LBM (men: R2 = 0.85, standard error of estimate [SEE] = 2.7 kg; women: R2 = 0.78, SEE = 2.2 kg), ASM (men: R2 = 0.81, SEE = 1.6 kg; women: R2 = 0.71, SEE = 1.2 kg), and BFM (men: R2 = 0.74, SEE = 2.7 kg; women: R2 = 0.83, SEE = 2.2 kg) according to sex. Compared with the first prediction equation, the addition of other factors, including serum creatinine level, physical activity, smoking status, and alcohol use, resulted in an R2 that is higher by 0.01 and SEE that is lower by 0.1. CONCLUSIONS: All equations had low bias, moderate agreement based on the Bland-Altman plot, and high ICC, and this result showed that these equations can be further applied to other epidemiologic studies.

• 적정기술학회지
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• 제7권2호
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• pp.225-234
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• 2021

이 논문의 목적은 국제개발협력의 유력한 전략으로 평가받고 있는 적정기술 사업화 모델을 라오스-한국 적정과학기술거점센터(LKSTC) 사례로 검토하는 것이다. LKSTC는 농식품 분야의 세척·수처리·살균기술, 재생에너지 분야의 피코 수력 발전기, 피코-태양광 하이브리드 시스템, 에너지 원격모니터링 기술을 개발했다. 적정기술 사업화는 카이펜 마을 기업, 학교기업, 사회적 기업을 창업했다. 정책적 시사점은 다음과 같다. 첫째, 개도국 적정기술 사업화는 수원국 정부의 지역개발 정책과 연계성을 높여야 한다. 둘째, 시장리스크를 최소화하기 위해 혁신적 기술개발 및 현지 창업네트워크를 적절히 구축해야 한다. 마지막으로 사업의 지속가능성을 높이기 위한 중장기적인 노력이 필요하다.

• Nuclear Engineering and Technology
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• 제53권6호
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• pp.1970-1978
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• 2021

The aim of this study was to optimize the target, moderator, and collimator (TMC) in a neutron beam generator for the accelerator-based BNCT (A-BNCT) system. The optimization employed the Monte Carlo Neutron and Photon (MCNP) simulation. The optimal geometry for the target was decided as the one with the highest neutron flux among nominates, which were called as angled, rib, and tube in this study. The moderator was optimized in terms of consisting material to produce appropriate neutron energy distribution for the treatment. The optimization of the collimator, which wrapped around the target, was carried out by deciding the material to effectively prevent the leakage radiations. As results, characteristic of the neutron beam from the optimized TMC was compared to the recommendation by the International Atomic Energy Agent (IAEA). The tube type target showed the highest neutron flux among nominates. The optimal material for the moderator and collimator were combination of Fluental (Al₂0₃+AlF₃) with ⁶⁰Ni filter and lead, respectively. The optimized TMC satisfied the IAEA recommendations such as the minimum production rate of epithermal neutrons from thermal neutrons: that was 2.5 times higher. The results can be used as source terms for shielding designs of treatment rooms.

• 문화기술의 융합
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• 제9권1호
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• pp.545-550
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• 2023

차량 충돌 시 벨트를 잡아당겨 탑승자의 상해 가능성을 최소화하기 위한 안전장치인 프리텐셔너는 화약 폭발 방식으로 구동되므로 화재나 파편이 튀는 2차 사고의 위험이 있으며 사고 발생 후 프리텐셔너 내부의 가스 발생기 뿐만 아니라 매니폴더를 포함한 연결 부품 모두를 교체해야 하는 단점이 있다. 따라서 본 논문에서는 안전하고 반영구적으로 사용이 가능한 탄성력 기반 프리텐셔너를 제안한다. 기존 프리텐셔너의 작동 원리를 열역학적/동역학적 관점으로 분석한 후 프리텐셔너 전개를 위해 필요한 가스 폭발에너지를 탄성에너지로 변환하였다. 또한 비감쇠 진동해석을 통해 프리텐셔너 작동시간을 확인하였으며 폭발 압력과 전개 시간 조건을 모두 만족하는 스프링 강성을 선정하였다. 스프링 부착 위치에 따른 차량 내부 설치 규격을 고려하여 코일 스프링 형상 및 고정부를 설계하였으며 제작을 통해 탄성력 기반 프리텐셔너의 성능 검증을 수행하였다.

• 한국지열·수열에너지학회논문집
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• 제18권4호
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• pp.12-21
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• 2022

Steam assisted gravity drainage(SAGD) is a process that drills well in the underground oil sands layer, injects hightemperature steam, lowers the viscosity of buried bitumen, and recovers it to the ground. Recently, direct contact steam generator(DCSG) is being developed to maximize steam efficiency for SAGD process. The DCSG requires high technology to achieve pressurized combustion and steam generation in accordance with underground pressurized conditions. Therefore, it is necessary to develop a combustion technology that can control the heat load and exhaust gas composition. In this study, process analysis of high-pressurized DCSG was conducted to apply oxygen enrichment technology in which nitrogen of the air was partially removed for increasing steam production and reducing fuel consumption. As the process analysis conditions, methane as the fuel and normal air or oxygen enriched air as the oxidizing agent were applied to high-pressurized DCSG process model. A simple combustion reaction program was used to calculate the property variations for combustion temperature, steam ratio and residual heat in exhaust gas. As a major results, the steam production efficiency of DCSG using the pure oxygen was about 6% higher than that of the normal air due to the reducing nitrogen in the air. The results of this study will be used as operating data to test the demonstration device.

• 한국산업정보학회논문지
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• 제28권5호
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• pp.77-87
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• 2023

재생 에너지 생성에서 중요한 역할을 하는 풍력 터빈은 작동 상태를 정확하게 평가하는 것이 에너지 생산을 극대화하고 가동 중지 시간을 최소화하는 데 매우 중요하다. 이 연구는 풍력 터빈 상태 진단을 위한 다양한 신경망 모델의 비교 분석을 수행하고 센서 측정 및 과거 터빈 데이터가 포함된 데이터 세트를 사용하여 효율성을 평가하였다. 분석을 위해 2MW 이중 여자 유도 발전기 기반 풍력 터빈 시스템(모델 HQ2000)에서 수집된 감시 제어 및 데이터 수집 데이터를 활용했다. 활성화함수, 은닉층 등을 고려하여 인공신경망, 장단기기억, 순환신경망 등 다양한 신경망 모델을 구축하였다. 대칭 평균 절대 백분율 오류는 모델의 성능을 평가하는 데 사용되었다. 평가를 바탕으로 풍력 터빈 상태 진단을 위한 신경망 모델의 상대적 효율성에 관한 결론이 도출되었다. 본 연구결과는 풍력발전기의 상태진단을 위한 모델선정의 길잡이가 되며, 고도의 신경망 기반 기법을 통한 신뢰성 및 효율성 향상에 기여하고, 향후 관련연구의 방향을 제시하는데 기여한다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.3464-3466
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• 2007

Power uprate is the process of increasing the maximum power level at which a commercial nuclear power plant may operate. Power uprate applications(113 units) for NPPs(Nuclear Power Plants) were recently approved in the United States. Utilities have been using power uprates since the 1970s as a way of increasing the power output of their nuclear plants. To increase the power output of a reactor, typically more highly enriched uranium fuel and/or more fresh fuel is used. This enables the reactor to produce more thermal energy and therefore more steam, driving a turbine generator to produce electricity. In this paper, the propriety of power uprate is explained through the review on the power uprate method and the changes of the physical parameters due to power uprate. The analysis results showed that the CDF(Core Damage Frequency) and LERF(Large Early Release Frequency) are affected in the current probabilistic safety assessment (PSA) model.