• 한국유체기계학회 논문집
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• 제10권3호
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• pp.39-46
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• 2007

This study presents a numerical procedure to optimize the shape of staggered dimple surface to enhance turbulent heat transfer in a rectangular channel. The RBNN method is used as an optimization technique with Reynolds-averaged Navier-Stokes analysis of fluid flow and heat transfer with shear stress transport (SST) turbulence model. The dimple depth-to-dimple print diameter (d/D), channel height-to-dimple print diameter ratio (H/D), and dimple print diameter-to-pitch ratio (D/S) are chosen as design variables. The objective function is defined as a linear combination of heat transfer related term and friction loss related term with a weighting factor. Latin Hypercube Sampling (LHS) is used to determine the training points as a mean of the design of experiment. The optimum shape shows remarkable performance in comparison with a reference shape.

• 한국기계가공학회지
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• 제14권3호
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• pp.85-91
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• 2015

The press-fit shaft is an important part used in automobiles, vessels, and trains. This study proposes an optimized design method to reduce damage that may occur in the press-fitted shaft by modifying the shape of the boss step of the press-fitted shaft. To reduce the time and cost of running the optimized design method, an approximate design optimization is applied and an optimized algorithm is generated using a genetic algorithm that is widely used in engineering fields and an approximate model using a response surface method. The planned experiments for the data that are needed to generate the approximate model use a central composite design (CCD) and Latin hypercube sampling (LHS), and the results of the approximate optimization using the above two design of experiments are to be compared.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.32-34
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• 2008

Latin Hypercube sampling strategy(LHS)는 출력변수에 의한 목적함수들의 기댓값의 추정을 위한 입력변수를 생성하는데 사용할 수 있는 샘플링 포인트 추출 방법으로, 샘플링 포인트의 "quality"를 향상시켜준다. multi-objective Pare optimization 에 근거한 LHS와 ($1+\lambda$) 진화기법으로 이루어진 최적화 algorithm을 제안 하였고, 이를 이용하여 6MW BLDC 전동기의 코깅토크를 최소화 하였다, 총 2단계의 최적 설계를 통해 초기형상의 코킹토크에 비해 19%로 감소하였다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1063-1068
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• 2008

A lens system of a camera module for mobile phones is comprised of the composition and design of various shapes of lens. To improve responses such as the modular transfer function (MTF), a lens system should always be constructed by considering uncertainty that can be caused by manufacturing and assembly error. In this study, tolerance optimization using the Latin Hypercube Sampling (LHS) technique is performed. In order to reduce the computational burden of the tolerance optimization process and decrease the influence from numerical noise effectively, we use the Progressive Quadratic Response Surface Modeling (PQRSM), which is one of Sequential Approximate Optimization (SAO) techniques. Using this method, we achieved optimal tolerance for each lens and obtained reliability for satisfying user‘s requirements. In addition, through the design process the manufacturing and assembly cost of a lens system was reduced.

• 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.

• 한국CDE학회논문집
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• 제15권1호
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• pp.24-32
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• 2010

This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.

• 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.

• 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).

• 한국수자원학회논문집
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• 제38권4호
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• pp.281-292
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• 2005

수자원장기종합계획에서는 물의 과부족 또는 가용한 물을 정량적으로 평가하기 위해 물수지 분석을 실시한다. 물수지 분석은 미래 예측되는 용수수요량과 공급가능량을 비교하는 단순한 과정이지만, 분석 과정에 포함되어 있는 자료와 모형의 불확실성으로 인하여 물수지 분석을 실시한 각종 보고서마다 서로 다른 결과를 보여주고 있어 국민의 신뢰를 얻지 못한 실정이다. 본 연구에서는 Monte Carlo simulation 기법 중 Latin Hypercube sampling에 기반한 확률적 모사로 물수지 분석에서의 불확실성을 표현하고 분석하였다. 대표 물수지 입력변수로 자연유량, 생공용수, 농업용수, 회귀율을 선정하여 이를 선형회귀와 entropy 이론으로 분포를 설정하였고, 불확실성 분석을 통하여 물부족량에 대한 불확실성의 범위와 위치를 규명하였다. 금강수계 3개의 소유역에 대해 불확실성 분석을 한 결과, 기존의 물수지 분석에서의 단일 물부족량이 과소 및 과대 추정될 수 있음을 보였고, 또한 민감도 분석을 통해 농업회귀율이 입력변수들 중 가장 큰 불확실성을 가지고 있으나 결과에는 거의 영향을 미치지 못하고 있음을 알 수 있었다.

• Nuclear Engineering and Technology
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• 제28권6호
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• pp.507-521
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• 1996

Quantification of uncertainties in the source term estimations by a large computer code, such as MELCOR and MAAP, is an essential process of the current Probabilistic safety assessment. The main objective of the present study is to investigate the applicability of a combined procedure of the response surface method (RSM) based on input determined from a statistical design and the Latin hypercube sampling (LHS) technique for the uncertainty analysis of CsI release fractions under a Hypothetical severe accident sequence of a station blackout at Younggwang nuclear power plant using MAAP3. OB code as a benchmark problem. On the basis of the results obtained in the present work, the RSM is recommended to be used as a principal tool for an overall uncertainty analysis in source term quantifications, while using the LHS in the calculations of standardized regression coefficients (SRC) and standardized rank regression coefficient (SRRC) to determine the subset of the most important input parameters in the final screening step and to check the cumulative distribution functions obtained by RSM. Verification of the response surface model for its sufficient accuracy is a prerequisite for the reliability of the final results that can be obtained by the combined procedure proposed in the present work.