• Transactions on Electrical and Electronic Materials
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• 제7권4호
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• pp.210-214
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• 2006

In this paper, two sampling methods which are Latin hypercube sampling (LHS) and simple random sampling were. compared to improve the modeling speed of neural network model. Sampling method was used to generate initial weights and bias set. Electrical characteristic data for $HfO_2$ thin film was used as modeling data. 10 initial parameter sets which are initial weights and bias sets were generated using LHS and simple random sampling, respectively. Modeling was performed with generated initial parameters and measured epoch number. The other network parameters were fixed. The iterative 20 minimum epoch numbers for LHS and simple random sampling were analyzed by nonparametric method because of their nonnormality.

• 전산구조공학
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• 제10권4호
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• pp.143-154
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• 1997

본 연구에서는 지하암반구조물의 구조해석시 불연속암반체의 물성변이를 고려할 수 있는 확률론적 해석기법을 개발하였다. 수치해석적 접근은 몬테칼로모사기법의 단점을 보완한 LHS기법을 사용하였고, 불연속면의 영향은 단층, 벽개 등과 같이 불연속성이 뚜렷한 지역에서 적용성이 높은 절리유한요소모델을 사용하였다. 재료특성에 대한 확률변수는 불연속면의 수직강성과 전단강성을 다확률변수로 사용하였으며, 이들은 확률공간에서 정규분포를 갖는 경우에 대하여 고려하였다. 본 연구에서 개발된 수치해석프로그램은 검증예제를 통하여 타당성을 확인하였으며, 가상의 불연속면군이 존재하는 지하원형공동에 대한 해석을 통하여 프로그램의 적용성을 확인하였다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2005년도 하계학술대회 논문집 Vol.6
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• pp.240-241
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• 2005

In this paper, Latin Hypercube Sampling based the neural network model for the electrical characteristics of $HfO_2$ thin films grown by metal organic molecular beam epitaxy was investigated. The accumulation capacitance and the hysteresis index are extracted to be the main responses to examine the characteristics of $HfO_2$ thin films. X-ray diffraction was used to analyze the characteristic variation for the different process conditions. The initial weights and biases are selected by Latin Hypercube Sampling method. This modeling methodology can allow us to optimize the process recipes and improve the manufacturability.

• 한국시뮬레이션학회논문지
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• 제32권3호
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• pp.67-74
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• 2023

반도체 제조라인(FAB)은 복잡하고 불확실한 운영환경에서 작동하는 대규모의 제조시스템 중 하나로 반도체 설비 운영을 담당하는 엔지니어들은 직관적이고 신속한 공정 스케줄링을 위해 가중치 기반 스케줄링을 널리 사용하고 있다. 가중치 기반 스케줄링에서 가중치 결정은 FAB 성능에 큰 영향을 미치므로 엔지니어들은 가중치 최적화를 위하여 시뮬레이션 기반 의사결정을 활용할 수 있다. 그러나 대규모 시뮬레이션은 많은 실험 비용을 요구하기 때문에 효과적인 의사결정을 위해서 신중한 실험설계가 요구된다. 본 연구에서는 적은 시뮬레이션 실행 내에서 효율적인 스케줄링을 도출하기 위해 세 가지 샘플링 대안(i.e., Optimal latin hypercube sampling(OLHS), Genetic algorithm(GA), and Decision tree based sequential search (DSS))에 대한 비교연구를 수행하였다. 시뮬레이션 실험을 통해 세 가지 대안이 단일 규칙보다 우수한 성능을 보였고, 그중 GA와 DSS가 최적화를 위한 효과적인 대안이 될 수 있음을 확인하였다.

• 한국CDE학회논문집
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• 제16권6호
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• pp.397-406
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• 2011

Since tolerance allocation in a mobile phone camera manufacturing process greatly affects production cost and reliability of optical performance, a systematic design methodology for allocating optimal tolerances is required. In this study, we proposed the tolerance optimization procedure for determining tolerances that minimize production cost while satisfying the reliability constraints on important optical performance indices. We employed Latin hypercube sampling for evaluating the reliabilities of optical performance and a function-based sequential approximate optimization technique that can reduce computational burden and well handle numerical noise in the tolerance optimization process. Using the suggested tolerance optimization approach, the optimal production cost was decreased by 30.3 % compared to the initial cost while satisfying the two constraints on the reliabilities of optical performance.

• 한국유체기계학회 논문집
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• 제12권3호
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• pp.7-12
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• 2009

In this paper, shape optimization based on three-dimensional flow analysis has been performed for impeller design of centrifugal compressor. To evaluate the objective function of an isentropic efficiency, Reynolds-averaged Navier-Stokes equations are solved with SST (Shear Stress Transport) turbulence model. The governing equations are discretized by finite volume approximations. The optimization techniques based on the radial basis neural network method are used for the optimization. Latin hypercube sampling as design of experiments is used to generate thirty design points within design space. Sequential quadratic programming is used to search the optimal point based on the radial basis neural network model. Four geometrical variables concerning impeller shape are selected as design variables. The results show that the isentropic efficiency is enhanced effectively from the shape optimization by the radial basis neural network method.

• Smart Structures and Systems
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• 제12권6호
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• pp.641-659
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• 2013

In this paper is studied the influence of the uncertain mass distribution over the floors on the choice of the optimal parameters of a hybrid control system for tall buildings subjected to wind load. In particular, an optimization procedure is developed for the robust design of a hybrid control system that is based on an enhanced Monte Carlo simulation technique and the genetic algorithm. The large computational effort inherent in the use of a MC-based procedure is reduced by the employment of the Latin Hypercube Sampling. With reference to a tall building modeled as a multi degrees of freedom system, several numerical analyses are carried out varying the parameters influencing the floors' masses, like the coefficient of variation of the distribution and the correlation between the floors' masses. The procedure allows to obtain optimal designs of the control system that are robust with respect to the uncertainties on the distribution of the dead and live loads.

• Water Engineering Research
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• 제3권4호
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• pp.215-234
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• 2002

Uncertainty in dam breach flood routing results was analyzed in order to provide the basis fer the investigation of their effects on the flood damage assessments and dam safety risk assessments. The Monte Carlo simulation based on Latin Hypercube Sampling technique was used to generate random values for two uncertain input parameters (i.e., dam breach parameters and Manning's n roughness coefficients) of a dam breach flood routing analysis model. The flood routing results without considering the uncertainty in two input parameters were compared with those with considering the uncertainty. This paper showed that dam breach flood routing results heavily depend on the two uncertain input parameters. This study indicated that the flood damage assessments in the downstream areas can be critical if uncertainty in dam breach flood routing results are considered in a reasonable manner.

• 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.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 학술대회
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• pp.229-232
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• 2008

This study presents a numerical procedure to optimize the shape of stepped circular pin-fins to enhance turbulent heat transfer. The KRG method is used as an optimization technique with Reynolds-averaged Navier-Stokes analysis of fluid flow and heat transfer with shear stress transport turbulent model. The objective function is defined as a linear combination of heat transfer and friction loss related terms with a weighting factor. Ten training points are obtained by Latin Hypercube Sampling for two design variables. Optimum shape has been successfully obtained with the increased objective function.