• Nuclear Engineering and Technology
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• 제42권6호
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• pp.690-703
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• 2010

Sampling based uncertainty analysis was carried out to quantify uncertainty in predictions of best estimate code RELAP5/MOD3.2 for a thermal hydraulic test (10% hot leg break LOCA) performed in the Large Scale Test Facility (LSTF) as a part of an IAEA coordinated research project. The nodalisation of the test facility was qualified for both steady state and transient level by systematically applying the procedures led by uncertainty methodology based on accuracy extrapolation (UMAE); uncertainty analysis was carried out using the Latin hypercube sampling (LHS) method to evaluate uncertainty for ten input parameters. Sixteen output parameters were selected for uncertainty evaluation and uncertainty band between $5^{th}$ and $95^{th}$ percentile of the output parameters were evaluated. It was observed that the uncertainty band for the primary pressure during two phase blowdown is larger than that of the remaining period. Similarly, a larger uncertainty band is observed relating to accumulator injection flow during reflood phase. Importance analysis was also carried out and standard rank regression coefficients were computed to quantify the effect of each individual input parameter on output parameters. It was observed that the break discharge coefficient is the most important uncertain parameter relating to the prediction of all the primary side parameters and that the steam generator (SG) relief pressure setting is the most important parameter in predicting the SG secondary pressure.

• 한국군사과학기술학회지
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• 제22권6호
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• pp.763-772
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• 2019

There is a need to use sheath flow nozzle to detect bioaerosol such as virus and bacteria due to their characteristics. In order to enhance the detection performance depending on nozzle parameters, numerical analysis was carried out using a commercial code, ANSYS CFX. Eulerian-lagrangian approach method is used in this simulation. Multiphase flow characteristics between primary fluid and solid were considered. The detection performance was evaluated based on the results of flow field in nozzle chamber such as focusing efficiency and swirl strength. In addition, Latin hypercube sampling(LHS) of design of experiment(DOE) was used for generating a near-random sampling. Then, the acceleration section is optimized using response surface method(RSM). Results show that the optimized model achieved a 6.13 % in a focusing efficiency and 11.47 % increase in swirl strength over the reference model.

• 한국군사과학기술학회지
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• 제22권4호
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• pp.527-535
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• 2019

Hanger in a rail-launched missile protrudes in general and causes to increase significant drag force. One method to avoid the significant increase of drag force is to apply fairings on the hanger. In this paper, sloping shaped fairing parameters of height, width, and length are optimized to minimize the drag force under subsonic speed region by examining three configurations of fairings : front-fairing only, rear-faring only, and the both front and rear fairing. We use Latin Hypercube Sampling method to determine the experimental points, and computational fluid dynamics with incompressible RANS solver was applied to acquire the data at sampling points. Then, we construct a meta model by kriging method. We find the best choice among three configurations examined : both front and rear fairing reduce the drag force by 63 % without the constraint of fairing mass, and front fairing reduced the drag force by 52 % with the constraint of hanger mass.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 춘계학술대회 논문요약집
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• pp.89-89
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• 2004

결정적인 알고리즘과 입력정보의 사용은 평가된 해석과 실제 시스템 값과의 차이로 잘못된 결론을 이끌지도 모른다. 실제 시스템은 대부분 각각의 입력 매개변수들(input parameters)과 관계된 넓은 공차 영역(tolerance band)을 가지고 있어서 입력정보로 하나의 단일한 값을 할당하는 것이 어렵다. 단일 입력에 대한 한가지 해는 변동의 이해 없이 제한된 값이라는 것을 인식할 필요가 있는데 대개 결정론적 설계는 형상과 관련된 치수변동, 항복강도나 부재의 밀도, 탄성계수와 같은 재료 물성치의 불확실성(uncertainty)과 시스템에 작용하는 하중의 변동 등을 직접 고려하지 않고 설계를 수행하기 때문에 수용할 수 있는 오차의 범위 안에서 시스템의 응답을 정확히 평가하기가 쉽지 않았다.(중략)

• Journal of Electrical Engineering and Technology
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• 제3권2호
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• pp.207-212
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• 2008

This paper presents a robust and computationally efficient optimal design algorithm for electromagnetic devices by combining an adaptive response surface approximation of the objective function and($1+{\lambda}$) evolution strategy. In the adaptive response surface approximation, the design space is successively reduced with the iteration, and Pareto-optimal sampling points are generated by using Latin hypercube design with the Max Distance and Min Distance criteria. The proposed algorithm is applied to an analytic example and TEAM problem 22, and its robustness and computational efficiency are investigated.

• Nuclear Engineering and Technology
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• 제35권5호
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• pp.387-398
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• 2003

For reference human intrusion scenarios constructed in previous study, a probabilistic safety assessment to derive the radionuclide concentration limits for the low- and intermediate- level radioactive waste disposal facility is conducted. Statistical approach by the Latin Hypercube Sampling method is introduced and new assumptions about the disposal facility system are examined and discussed. In our previous study of deterministic approach, the post construction scenarios appeared as most limiting scenario to derive the radionuclide concentration limits. Whereas, in this statistical approach, the post drilling and the post construction scenarios are mutually competing for the scenario selection according to which radionuclides are more important in safety assessment context. Introduction of new assumption shows that the post drilling scenario can play an important role as the limiting scenario instead of the post-construction scenario. When we compare the concentration limits between the previous and this study, concentrations of radionuclides such as Nb-94, Cs-137 and alpha-emitting radionuclides show elevated values than the case of the previous study. Remaining radionuclides such as Sr-90, Tc-99 I-129, Ni-59 and Ni-63 show lower values than the case of the previous study.

• JSTS:Journal of Semiconductor Technology and Science
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• 제15권1호
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• pp.101-113
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• 2015

The Monte-Carlo (MC) technique is very efficient solution for statistical problem. Various MC methods can easily be applied to statistical circuit performance analysis. Recently, as the number of process parameters and their impact, has increasingly affected circuit performance, a sufficient sample size is required in order to consider high dimensionality, profound nonlinearity, and stringent accuracy requirements. Also, it is important to identify the performance of circuit as soon as possible. In this paper, Fast MC method is proposed for efficient analysis of circuit performance. The proposed method analyzes performance using enhanced-precision Latin Hypercube Sampling Monte Carlo (LHSMC). To increase the accuracy of the analysis, we calculate the effective dimension for the low discrepancy value on critical parameters. This will guarantee a robust input vector for the critical parameters. Using a 90nm process parameter and OP-AMP, we verified the accuracy and reliability of the proposed method in comparison with the standard MC, LHS and Quasi Monte Carlo (QMC).

• 한국전자통신학회논문지
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• 제15권5호
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• pp.949-958
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• 2020

차량을 구성하는 엔진, 미션, 현가, 제동, 조향장치 등 다양한 장치 중에서 현가 장치는 타이어와 차체 사이에 설치되어 노면에 의한 차량의 진동을 억제하여 승차감을 향상시키고 차륜과 노면 사이에 적절한 접지력을 유지시켜 차량의 조정안정성을 향상시키는 등 차량역학적인 측면에서 많은 영향을 미치는 장치 중의 하나이다. 본 연구에서는 차량용 현가 장치의 충격 흡수기를 실제 특성과 유사한 상세 모델로 모델링하고, 충격 흡수기의 주요 설계변수의 불확실성을 통계적으로 고려하여 설계변수의 불확실성이 현가 장치의 동적 특성에 미치는 영향에 대하여 연구하였다.

• Nuclear Engineering and Technology
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• 제52권7호
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• pp.1587-1596
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• 2020

The location selection for nuclear power plants (NPP) is a strategic decision, which has significant impact operation of the plant and sustainable development of the region. Further, the ranking of the alternative locations and selection of the most suitable and efficient locations for NPPs is an important multi-criteria decision-making problem. In this paper, the non-sequential Monte Carlo probabilistic method and the Latin hypercube sampling probabilistic method are used to evaluate and select the optimal locations for NPP. These locations are identified by the power plant's onsite loads and the average of the lowest number of relay protection after the NPP's trip, based on electricity considerations. The results obtained from the proposed method indicate that in selecting the optimal location for an NPP after a power plant trip with the purpose of internal onsite loads of the power plant and the average of the lowest number of relay protection power system, on the IEEE RTS 24-bus system network given. This paper provides an effective and systematic study of the decision-making process for evaluating and selecting optimal locations for an NPP.

• 대한기계학회논문집A
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• 제29권9호
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• pp.1199-1208
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• 2005

Nowadays, it is performed actively to optimize by using an approximate model. This is called the approximate optimization. In addition, the sequential approximate optimization (SAO) is the repetitive method to find an optimum by considering the convergence of an approximate optimum. In some recent studies, it is proposed to increase the fidelity of approximate models by applying the sequential sampling. However, because the accuracy and efficiency of an approximate model is directly connected with the design area and the termination criteria are not clear, sequential sampling method has the disadvantages that could support an unreasonable approximate optimum. In this study, the SAO is executed by using trust region, Kriging model and Optimal Latin Hypercube design (OLHD). Trust region is used to guarantee the convergence and Kriging model and OLHD are suitable for computer experiment. finally, this SAO method is applied to various optimization problems of highly nonlinear mathematical functions. As a result, each approximate optimum is acquired and the accuracy and efficiency of this method is verified by comparing with the result by established method.