• Title/Summary/Keyword: Latin hypercube

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Stochastic Finite Element Analysis of Underground Structure Considering the Multi-Random Variables in the Physical Properties of Rock mass (다확률변수를 고려한 불확정 지하구조계의 확률론적 유한요소해석)

  • 최규섭;정영수;황신일
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1996.04a
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    • pp.173-181
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    • 1996
  • In this study, a stochastic finite element model is proposed with a view to consider the uncertainty of physical properties of rock mass in the analysis of structural behavior on underground caverns. Here, the Latin Hypercube Sampling technique, in which can makeup weak points of the Monte Carlo Simulation, is applied for the analysis of underground cavern. The validity of the newly developed computer program has been confirmed in terms of verification examples. And, the applicability of the program to the field has been tested in terms of the analysis of the underground oil storage cavern in korea.

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Shape Optimization of Cylindrical Film-Cooling Hole Using Kriging Method (크리깅 기법을 이용한 원통형 막냉각 홀의 최적설계)

  • Lee, Ki-Don;Kim, Kwang-Yong
    • Proceedings of the KSME Conference
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    • 2008.11b
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    • pp.2729-2732
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    • 2008
  • Cylindrical film-cooling hole is formulated numerically and optimized to enhance film-cooling effectiveness. The Kriging method is used an optimization technique with Reynolds-averaged Navier-Stokes analysis of fluid and heat transfer with shear stress transport model. The hole length-to-diameter ratio and injection angle are chosen as design variables and spatially averaged film-cooling effectiveness is considered as objective function which is to be maximized. Twelve training points obtained by Latin Hypercube Sampling for two design variables. Optimum shape shows the film-cooling effectiveness increased.

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Design Optimization of a Cylindrical Film-Cooling Hole Using Neural Network Techniques (신경회로망기법을 사용한 원통형 막냉각 홀의 최적설계)

  • Lee, Ki-Don;Kim, Kwang-Yong
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.32 no.12
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    • pp.954-962
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    • 2008
  • This study presents a numerical procedure to optimize the shape of cylindrical cooling hole to enhance film-cooling effectiveness. 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 turbulent model. The hole length-to-diameter ratio and injection angle are chosen as design variables and film-cooling effectiveness is considered as objective function which is to be maximized. Twelve training points are obtained by Latin Hypercube Sampling for two design variables. In the sensitivity analysis, it is found that the objective function is more sensitive to the injection angle of hole than the hole length-to diameter ratio. Optimum shape gives considerable increase in film-cooling effectiveness.

Surrogate Modeling for Optimization of a Centrifugal Compressor Impeller

  • Kim, Jin-Hyuk;Choi, Jae-Ho;Kim, Kwang-Yong
    • International Journal of Fluid Machinery and Systems
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    • v.3 no.1
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    • pp.29-38
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    • 2010
  • This paper presents a procedure for the design optimization of a centrifugal compressor. The centrifugal compressor consists of a centrifugal impeller, vaneless diffuser and volute. And, optimization techniques based on the radial basis neural network method are used to optimize the impeller of a centrifugal compressor. The Latin-hypercube sampling of design-of-experiments is used to generate the thirty design points within design spaces. Three-dimensional Reynolds-averaged Navier-Stokes equations with the shear stress transport turbulence model are discretized by using finite volume approximations and solved on hexahedral grids to evaluate the objective function of the total-to-total pressure ratio. Four variables defining the impeller hub and shroud contours are selected as design variables in this optimization. The results of optimization show that the total-to-total pressure ratio of the optimized shape at the design flow coefficient is enhanced by 2.46% and the total-to-total pressure ratios at the off-design points are also improved significantly by the design optimization.

A Study of Cogging Torque Minimization for a Outer-Rotor Type Small BLDC Motor by using Latin Hypercube Sampling strategy (LHS를 이용한 소형 다상 외전형 BLDC 전동기의 코깅토크 최소화 연구)

  • Woo, Sung-Hyun;Chung, Hyun-Koo;Kim, Young-Bae;Jang, Hyeong-Taek;Shin, Pan-Seok;Kong, Yeong-Kyung
    • Proceedings of the KIEE Conference
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    • 2009.04b
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    • pp.64-66
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    • 2009
  • 소형 다상 의전형 BLDC 전동기의 코깅토크를 최소화하기 위해 코깅토크의 발생원인 중 하나인 고정자 슬롯의 형상에 샘플링 포인트 기법인 LHS를 이용한 최적화 알고리즘을 적용하여 코깅토크를 최소화하는 최적 설계를 수행 하였다. 총 3번의 반복계산을 하여 코깅토크가 최소화 되는 최적점을 계산한 결과, 최대 코깅 토크가 1.07 [N.m]에서 0.75 [N.m]로, 초기 형상의 약 70%로 감소되었다.

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Neural network modeling of Pretilt Angle on the Homogeneous Polyimide Surface (신경망을 이용한 공정변수에 따른 수평 폴리머 표면의 경사각에 관한 연구)

  • Lee, Jung-Hwan;Ko, Young-Don;Kang, Hee-Jin;Seo, Dae-Shik;Yun, Il-Gu
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2006.06a
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    • pp.426-427
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    • 2006
  • In this paper, the neural network model of the pretilt angle in the nematic liquid crystal on the homogeneous polyimide surface with different surface treatments is investigated. The pretilt angle is one of the main factors to determine the alignment of the liquid crystal display. The pretilt angle is measured to analyze the variation of the characteristics on the various process conditions. The rubbing strength and the hard baking temperature are considered as input factors. Latin hypercube sampling was used to generate initial weights and biases.

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Assessing the Feasibility of an Accident Management Strategy Using Dynamic Reliability Methods

  • Moosung Jae;Kim, Jae-Hwan
    • Nuclear Engineering and Technology
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    • v.29 no.1
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    • pp.1-6
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    • 1997
  • This paper presents a new dynamic approach for assessing feasibility associated with the implementation of accident management strategies by the operators. This approach includes the combined use of both the concept of reliability physics and a dynamic event tree generation scheme. The reliability physics is based on the concept of a comparison between two competing variables, i.e., the requirement and the achievement parameter, while the dynamic event tree generation scheme on the continuous generation of the possible event sequences at every branch point up to the desired solution. This approach is applied to a cavity flooding strategy in a reference plant, which is to supply water into the reactor cavity using emergency fire systems in the station blackout sequence. The MAAP code and Latin Hypercube sampling technique are used to determine the uncertainty of the requirement parameter. It has been demonstrated that this combined methodology may contribute to assessing the success likelihood of the operator actions required during accidents and therefore to developing the accident management procedures.

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Assessment of three optimization techniques for calibration of watershed model

  • Birhanu, Dereje;Kim, Hyeonjun;Jang, Cheolhee;Park, Sanghyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.428-428
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    • 2017
  • In this study, three optimization techniques efficiency is assessed for calibration of the GR4J model for streamflow simulation in Selmacheon, Boryeong Dam and Kyeongancheon watersheds located in South Korea. The Penman-Monteith equation is applied to estimate the potential evapotranspiration, model calibration, and validation is carried out using the readily available daily hydro-meteorological data. The Shuffled Complex Evolution-University of Arizona(SCE-UA), Uniform Adaptive Monte Carlo (UAMC), and Coupled Latin Hypercube and Rosenbrock (CLHR) optimization techniques has been used to evaluate the robustness, performance and optimized parameters of the three catchments. The result of the three algorithms performances and optimized parameters are within the recommended ranges in the tested watersheds. The SCE-UA and CLHR outputs are found to be similar both in efficiency and model parameters. However, the UAMC algorithms performances differently in the three tested watersheds.

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A New Dynamic HRA Method and Its Application

  • Jae, Moosung
    • International Journal of Reliability and Applications
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    • v.2 no.1
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    • pp.37-48
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    • 2001
  • This paper presents a new dynamic human reliability analysis method and its application for quantifying the human error probabilities in implementing management action. For comparisons of current HRA methods with the new method, the characteristics of THERP, HCR, and SLIM-MAUD, which are most frequency used method in PSAs, are discussed. The action associated with implementation of the cavity flooding during a station blackout sequence is considered for its application. This method is based on the concepts of the quantified correlation between the performance requirement and performance achievement. The MAAP 3.0B code and Latin Hypercube sampling technique are used to determine the uncertainty of the performance achievement parameter. Meanwhile, the value of the performance requirement parameter is obtained from interviews. Based on these stochastic obtained, human error probabilities are calculated with respect to the various means and variances of the things. It is shown that this method is very flexible in that it can be applied to any kind of the operator actions, including the actions associated with the implementation of accident management strategies.

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A surrogate model for the helium production rate in fast reactor MOX fuels

  • D. Pizzocri;M.G. Katsampiris;L. Luzzi;A. Magni;G. Zullo
    • Nuclear Engineering and Technology
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    • v.55 no.8
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    • pp.3071-3079
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    • 2023
  • Helium production in the nuclear fuel matrix during irradiation plays a critical role in the design and performance of Gen-IV reactor fuel, as it represents a life-limiting factor for the operation of fuel pins. In this work, a surrogate model for the helium production rate in fast reactor MOX fuels is developed, targeting its inclusion in engineering tools such as fuel performance codes. This surrogate model is based on synthetic datasets obtained via the SCIANTIX burnup module. Such datasets are generated using Latin hypercube sampling to cover the range of input parameters (e.g., fuel initial composition, fission rate density, and irradiation time) and exploiting the low computation requirement of the burnup module itself. The surrogate model is verified against the SCIANTIX burnup module results for helium production with satisfactory performance.