• Title/Summary/Keyword: Latin Hypercube sampling

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Optimization of a Cooling Channel with Staggered Elliptical Dimples Using Neural Network Techniques (신경회로망기법을 사용한 타원형 딤플유로의 냉각성능 최적화)

  • Kim, Hyun-Min;Moon, Mi-Ae;Kim, Kwang-Yong
    • The KSFM Journal of Fluid Machinery
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    • v.13 no.6
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    • pp.42-50
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    • 2010
  • The present analysis deals with a numerical procedure for optimizing the shape of elliptical dimples in a cooling channel. The three-dimensional Reynolds-averaged Navier-Stokes (RANS) analysis is employed in conjunction with the SST model for predictions of the turbulent flow and the heat transfer. Three non-dimensional geometric design variables, such as the ellipse dimple diameter ratio, ratio of the dimple depth to the average diameter, and ratio of the distance between dimples to the pitch are considered in the optimization. Twenty-one experimental points within design space are selected by Latin Hypercube Sampling. Each objective function values at these points are evaluated by RANS analysis and producing optimal point using surrogate model. The linear combination of heat transfer coefficient and friction loss related terms with a weighting factor is defined as the objective function. The results show that the optimized elliptical dimple shape improves considerably the heat transfer performance than the circular dimple shape.

Uncertainty quantification of once-through steam generator for nuclear steam supply system using latin hypercube sampling method

  • Lekang Chen ;Chuqi Chen ;Linna Wang ;Wenjie Zeng ;Zhifeng Li
    • Nuclear Engineering and Technology
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    • v.55 no.7
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    • pp.2395-2406
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    • 2023
  • To study the influence of parameter uncertainty in small pressurized water reactor (SPWR) once-through steam generator (OTSG), the nonlinear mathematical model of the SPWR is firstly established. Including the reactor core model, the OTSG model and the pressurizer model. Secondly, a control strategy that both the reactor core coolant average temperature and the secondary-side outlet pressure of the OTSG are constant is adopted. Then, the uncertainty quantification method is established based on Latin hypercube sampling and statistical method. On this basis, the quantitative platform for parameter uncertainty of the OTSG is developed. Finally, taking the uncertainty in primary-side flowrate of the OTSG as an example, the platform application work is carried out under the variable load in SPWR and step disturbance of secondary-side flowrate of the OTSG. The results show that the maximum uncertainty in the critical output parameters is acceptable for SPWR.

Uncertainty of Time-Dependent Effects in Concrete Structures (콘크리트 구조물의 시간 의존적 효과의 불확실성)

  • Yang, In-Hwan
    • Proceedings of the Korea Concrete Institute Conference
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    • 2006.05a
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    • pp.462-465
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    • 2006
  • This paper is aimed at proposing the sampling method to reduce variance of statistical parameters in uncertainty analysis of concrete structures. The proposed method is a modification of Latin Hypercube sampling method. This uses specially modified tables of random permutations of rank number. Also, the Spearman coefficient is used to make modified tables. Numerical analysis is carried out to predict the uncertainty of axial shortening in prestressed concrete bridge. The numerical results show that the method is efficient for uncertainty analysis of complex structural system such as prestressed concrete bridges.

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Quantifying Uncertainty for the Water Balance Analysis (물수지 분석을 위한 불확실성 정량화)

  • Lee, Seung-Uk;Kim, Young-Oh;Lee, Dong-Ryul
    • Journal of Korea Water Resources Association
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    • v.38 no.4 s.153
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    • pp.281-292
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    • 2005
  • The water balance analysis for the long-term water resources plan is a simple calculation that compares water demands with possible water supplies. For a watershed being considered the reports on the performance of the water balance analysis, however, have shown inconsistent results and thus have not earned credibility due to the uncertainty of the data acquired and models used. In this research, uncertainties in the water scarcity estimate were assessed through probability representation based on the Monte Carlo simulation using Latin Hypercube Sampling (LHS). The natural flow, municipal demand, industrial demand, agricultural demand, and return flow rate were selected as representative input variables for the water balance analysis, and their distributions were set based on the linear regression and the entropy theory. The statistical properties of the output variable samples were analyzed in comparison with a deterministic estimate of the water scarcity of an existing study. Application of LHS to three sub-basins of the Geum river basin showed the deterministic estimate could be overestimated or underestimated. The sensitivity analysis as well as the uncertainty analysis found that the return flow rate of the agricultural water is the most uncertain but is rarely sensitive to the output of the water balance analysis.

Reliability Design using Asymptotic Variance of Inverse Cumulative Distribution Function (분위수의 점근적 분산을 이용한 신뢰성 설계)

  • Cho H.J.;Baek S.H.;Hong S.H.;Cho S.S.;Joo W.S.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.1682-1685
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    • 2005
  • System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolerance of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or estimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte-Carlo Method and got the probabilistic sensitivity. The sensitivity of structural response with respect to inconstant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

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Assessment Of Radionuclide Release Rates From The Engineered Barriers And The Quantification Of Their Uncertainties For A Low- And Intermediate-Level Radioactive Waste Repository (방사성폐기물처분장 인공방벽으로부터의 핵종유출률 평가 및 불확실도 정량화)

  • Cho, W.J.;Lee, J.O.;Hahn, P.S.;Park, H.H.
    • Nuclear Engineering and Technology
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    • v.26 no.1
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    • pp.78-89
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    • 1994
  • The radionuclide release rates from the engineered barrier composed of concrete structure and clay-based backfill in a low and intermediate level waste repository were assessed. Four types of release pathway were considered, and the contribution of each pathway to the total release were analyzed. To quantify the effect of uncertainties of input parameter values on the assessment of radionuclide release rates, the Latin Hypercube sampling method was used, and the resulting release rate distribution were determined through a goodness-of-fit test. Finally, the ranges of maxi-mum release rates ore estimated statistically with a confidence level of 95%.

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A Permanent Magnet Pole Shape Optimization for a 6MW BLDC Motor by using Response Surface Method (I) (RSM을 이용한 6MW BLDC용 영구자석의 형상 최적화 연구 (I))

  • Woo, Sung-Hyun;Chung, Hyun-Koo;Shin, Pan-Seok
    • Proceedings of the KIEE Conference
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    • 2008.04c
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    • pp.65-67
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    • 2008
  • An adaptive response surface method with Latin Hypercube sampling strategy is employed to optimize a magnet pole shape of large scale BLDC motor to minimize the cogging torque. The proposed algorithm consists of the multi-objective Pareto optimization and ($1+{\lambda}$) evolution strategy to find the global optimal points with relatively fewer sampling data. In the adaptive RSM, an adaptive sampling point insertion method is developed utilizing the design sensitivities computed by using finite element method to set a reasonable response surface with a relatively small number of sampling points. The developed algorithm is applied to the shape optimization of PM poles for 6MW BLDC motor.

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A Permanent Magnet Pole Shape Optimization for a 6MW BLDC Motor by using Response Surface Method (II) (RSM을 이용한 6MW BLDC용 영구자석의 형상 최적화 연구 (II))

  • Woo, Sung-Hyun;Chung, Hyun-Koo;Shin, Pan-Seok
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.701-702
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    • 2008
  • An adaptive response surface method with Latin Hypercube sampling strategy is employed to optimize a magnet pole shape of large scale BLDC motor to minimize the cogging torque. The proposed algorithm consists of the multi-objective Pareto optimization and (1+${\lambda}$) evolution strategy to find the global optimal points with relatively fewer sampling data. In the adaptive RSM, an adaptive sampling point insertion method is developed utilizing the design sensitivities computed by using finite element method to get a reasonable response surface with a relatively small number of sampling points. The developed algorithm is applied to the shape optimization of PM poles for 6 MW BLDC motor, and the cogging torque is reduced to 19% of the initial one.

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A Study on A Dynamic Reliability Analysis Model (동적신뢰도 평가모델의 연구)

  • 제무성
    • Proceedings of the Korean Reliability Society Conference
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    • 2000.04a
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    • pp.239-246
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    • 2000
  • 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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A New Dynamic HRA Method and Its Application (새로운 동적인간신뢰도 방법론과 적용)

  • Jae, Moo-Sung;Park, Chan-Kue
    • Nuclear Engineering and Technology
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    • v.27 no.3
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    • pp.292-300
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    • 1995
  • This paper present a new dynamic HRA (Human Reliability Analysis) method and its application for Quantifying the human error probabilities in implementing an accident management action. For comparisons of current HRA methods with the new method, the characteristics of THERP, HCR, and SLIM-MAUD, which are most frequently used methods in PSAs, are discussed. The action associated with the 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 distributions obtained, human error probabilities are calculated with respect to the various means and variances of the timings. 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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