• 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.

• 대한전기학회논문지:전력기술부문A
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• 제55권1호
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• pp.45-51
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• 2006

This paper proposes a method to evaluate the Total Transfer Capability (TTC) by considering uncertainty of weather conditions. TTC is limited not only by the violation of system thermal and voltage limits, but also restricted by transient stability limit. Impact of the contingency on the power system performance could not be addressed in a deterministic way because of the random nature of the system equipment outage and the increase of outage probability according to the weather conditions. For these reasons, probabilistic approach is necessary to realize evaluation of the TTC. This method uses a sequential Monte Carlo simulation (MCS). In sequential simulation, the chronological behavior of the system is simulated by sampling sequence of the system operating states based on the probability distribution of the component state duration. Therefore, MCS is used to accomplish the probabilistic calculation of the TTC with consideration of the weather conditions.

• 한국응용곤충학회지
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• 제54권3호
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• pp.159-167
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• 2015

파프리카(Capsicum annuum var. angulosum)의 주요해충인 담배가루이(Bemisia tabaci)의 고정 정확도 수준에서 표본조사법(Fixedprecision sampling plan)을 개발하였다. 개발된 표본 조사법은 파프리카 온실의 담배가루이 방제체계 확립을 위해 공간분포분석, 표본추출 정시선 그리고 의사결정법으로 이루어 졌다. 자료 수집은 식물체를 상단(지상으로부터 180-220 cm), 중단(지상으로부터 80-120 cm), 하단(지상으로부터 30-70 cm)로 나누어 각 위치별 3개의 파프리카 잎에서 담배가루이 성충, 번데기를 관찰하고 그 총 수를 기록하였다. 담배가루이 성충은 식물체의 상부에서 움직이고 신초에 주로 산란하며 일정부분이 하단으로 내려오기 때문에 상단과 하단에 많이 분포하였으며, 번데기의 경우 상부에 알을 낳았지만 식물체가 크면서 알을 낳은 잎이 아랫부분이 되고 부화한 유충은 잎 뒤에 고착 상태로 우화까지 움직임이 거의 없기 때문에 중단과 하단에서 많이 분포하였다. 공간분포분석은 Taylor's power law (TPL)를 이용하였으며, TPL계수의 차이를 공분산분석(ANCOVA)하여 차이가 없는 경우 자료를 통합하여 계산된 새 TPL 상수값을 이용하여 표본추출 정시선을 구하였다. 그리고 담배가루이 성충과 번데기의 방제밀도수준을 2.0마리와 10.0마리로 설정하여 방제의사를 결정하였다. 마지막으로 분석에 사용하지 않은 독립된 자료를 이용하여 개발된 표본추출법의 유효성을 Resampling Validation for Sampling Plan (RVSP) 프로그램으로 평가한 결과 적합한 정확도를 보였다.

• 한국기계가공학회지
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• 제19권6호
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• pp.55-60
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• 2020

The injection molding technique is a processing method widely used for the production of plastic parts. In this study, the gate position, gate size, packing time, and melt temperature were optimized to minimize both the stress and deformation that occur during the injection molding process of medical suction device components. We used a central composite design and Latin hypercube sampling to acquire the data and adopted the response surface method as an approximation method. The efficiency of the optimization of the injection molding problem was determined by comparing the results of a genetic algorithm, sequential quadratic programming, and a non-dominant classification genetic algorithm.

• Journal of Mechanical Science and Technology
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• 제20권8호
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• pp.1169-1182
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• 2006

Robust design technology has been applied to versatile engineering problems to ensure consistency in product performance. Since 1980s, the concept of robust design has been introduced to numerical optimization field, which is called the robust optimization. The robustness in the robust optimization is determined by a measure of insensitiveness with respect to the variation of a response. However, there are significant difficulties associated with the calculation of variations represented as its mean and variance. To overcome the current limitation, this research presents an implementation of the approximate statistical moment method based on kriging metamodel. Two sampling methods are simultaneously utilized to obtain the sequential surrogate model of a response. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method. Then, the simulated annealing algorithm of global optimization methods is adopted to find the global robust optimum. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.

• 분석과학
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• 제18권4호
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• pp.344-354
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• 2005

최근 들어 실내공기질 악화의 주 오염원인 건축자재에 대한 관심이 고조되면서 건축자재 오염물질 방출시험 자료 구축이 중요하게 됨에 따라, 신뢰성 있는 자료 확보를 위해 건축자재 방출시험 정도 관리에 대한 필요성이 대두되었다. 이에 본 연구는 건축자재 방출시험 성능에 대한 정도관리를 위해 총 휘발성 유기화합물과 포름알데히드에 대하여 기기분석 재현성, 회수율, 검출한계, 중복 및 반복채취 재현성, 파과용량 평가 등을 실시하였다. 기기분석 및 시료채취에 대한 재현성은 20~30% 이내의 양호한 결과를 보였으며, 회수율은 80% 이상으로 나타났으며, 파과 역시 일어나지 않아 소형챔버법에 의한 성능은 전반적으로 만족할 만한 수준을 보였다. 따라서, 소형챔버를 이용한 건축자재 오염물질 방출시험방법은 신뢰성있는 자료를 제공해 줄 수 있을 것으로 판단된다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.2666-2671
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• 2007

This work presents microchannel heat sink shape optimization procedure using Kriging method. Design variables relating to microchannel width, depth and fin width are selected, and thermal resistance has been taken as objective function. Design points are selected through a three-level fractional factorial design of sampling method. Navier-Stokes and energy equations for laminar flow and conjugate heat transfer are solved at these design points using a finite volume solver. Solutions are carefully validated with experimental results. Using the numerically evaluated objective function, a surrogate model (Kriging) is constructed and optimum point is searched by sequential quadratic programming. The process of shape optimization greatly improves the thermal performance of microchannel heat sink under constant pumping power.

• 대한기계학회논문집B
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• 제31권9호
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• pp.733-740
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• 2007

Microchannel heat sink shape optimization is performed using Kriging method. Design variables relating to microchannel width, depth and fin width are selected, and thermal resistance has been taken as objective function. Design points are selected through a three-level fractional factorial design of sampling method. Navier-Stokes and energy equations for laminar flow and conjugate heat transfer are solved at these design points using a finite volume solver. Solutions are carefully validated with experimental results. Using the numerically evaluated objective function, a surrogate model (Kriging) is constructed and optimum point is searched by sequential quadratic programming. The process of shape optimization greatly improves the thermal performance of microchannel heat sink under constant pumping power.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1169-1175
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• 2008

The validation technique is classified with two methods whether to demand of additional experimental points. The method which requires additional experimental points such as RSME is actually impossible in engineering field. Therefore, the method which only use experimented points such as the cross validation technique is only available. But the cross validation not only requires considerable computational costs for generating metamodel each iterations, but also cannot measure quantitatively the fidelity of metamodel. In this research we propose a new validation technique for representative metamodels using an variance of metamodel and confidence interval information. The proposed validation technique computes confidence intervals using a variance information from the metamodel. This technique will have influence on choosing the accurate metamodel, constructing ensemble of each metamodels and advancing effectively sequential sampling technique.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2004년도 추계학술대회
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• pp.221-229
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• 2004

Recently, there has been enormous growth in the amount of commercial and scientific data, such as protein sequences, retail transactions, and web-logs. Such datasets consist of sequence data that have an inherent sequential nature. However, only a few of the existing clustering algorithms consider sequentiality. This study presents a method for clustering such sequence datasets. The similarity between sequences must be decided before clustering the sequences. This study proposes a new similarity measure to compute the similarity between two sequences using a sequence element. Two clustering algorithms using the proposed similarity measure are proposed: a hierarchical clustering algorithm and a scalable clustering algorithm that uses sampling and a k-nearest neighbor method. Using a splice dataset and synthetic datasets, we show that the quality of clusters generated by our proposed clustering algorithms is better than that of clusters produced by traditional clustering algorithms.