• 의료ㆍ복지 건축 : 한국의료복지건축학회 논문집
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• 제23권1호
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• pp.7-14
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• 2017

Purpose: Since the large hospitals are one of the most intensive energy users among building types in Korea, it is important to investigate and apply appropriate energy conservation measures. There are many researches on energy conservation measures for HVAC system in hospitals, but only few useful guidelines for envelope design variables were existed. The building envelope is one of the important factors to building energy consumption and patients' comfort. The purpose of this study is to suggest the most influential envelope design variables for each end-use energy demand. Methods: 100 samples were generated by LHS(Latin Hypercube Sampling) method. After energy performance simulation, global sensitivity analysis was performed by the regression method. DesignBuilder, Simlab 2.2 and JEPlus were used in this process. Results: The most influencing variables are SHGC, SHGC and VT for heating, cooling, and lighting, respectively. However, the most influencing variable for total energy demand is WWR(Window to Wall Ratio). The analysis was conducted based on the coefficient of variance results. Implications: The six envelop design variables were ranked according to the end-use energy demand.

• Earthquakes and Structures
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• 제17권5호
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• pp.463-475
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• 2019

In this paper, a procedure to develop fragility curves of structures equipped with semi-active tuned mass dampers (SATMDs) considering multiple failure criteria has been presented while accounting for the uncertainties of the input excitation, structure and control device parameters. In this procedure, Latin hypercube sampling (LHS) method has been employed to generate 30 random SATMD-structure systems and nonlinear incremental dynamic analysis (IDA) has been conducted under 20 earthquakes to determine the structural responses, where failure probabilities in each intensity level have been evaluated using Monte Carlo simulation (MCS) method. For numerical analysis, an eight-story nonlinear shear building frame with bilinear hysteresis material behavior has been used. Fragility curves for the structure equipped with optimal SATMDs have been developed considering single and multiple failure criteria for different performance levels and compared with that of uncontrolled structure as well as structure controlled using passive tuned mass damper (TMD). Numerical analysis has shown the capability of SATMDs in significant enhancement of the seismic fragility of the nonlinear structure. Also, considering multiple failure criteria has led to increasing the fragility of the structure. Moreover, it is observed that the influence of the uncertainty of input excitation with respect to the other uncertainties is considerable.

• 한국전산구조공학회논문집
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• 제28권4호
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• pp.351-359
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• 2015

구조물의 붕괴성능을 정확하게 평가하기 위해서는 구조물과 관련된 구조부재 및 지반운동의 불확실성을 고려한 확률적 접근방식이 요구된다. 불확실성의 종류에 상관없이 불확실성은 구조물의 응답에 영향을 미치게 되는데, 구조물의 성능목표를 설정함에 있어 이러한 불확실성 전파를 예측할 필요가 있다. 최근 들어, 구조물의 붕괴성능을 평가하는 방법으로 사용되고 있는 증분동적해석은 지반운동과 관련된 임의적 불확실성을 해석과정에서 고려할 수 있다는 장점이 있으나, 확률론적 평가를 위한 또 다른 중요 요인인 인식론적 불확실성을 직접적으로 평가할 수 없다는 제한사항이 있다. 본 연구에서는 철골모멘트골조를 표본 건물로 선정하여 인식론적 불확실 요인으로 정의한 구조물의 고유감쇠, 지진중량, 구조부재의 항복강도 및 탄성계수가 구조물의 붕괴성능에 미치는 영향을 확률적으로 평가하였다. 이를 위하여 라틴 방격 추출법을 사용한 몬테카를로 시뮬레이션을 통해 증분동적해석을 수행하여 구조시스템 붕괴성능의 변동성을 정량적으로 예측하였다. 해석결과, 붕괴성능의 변동성에 인식론적 불확실성을 대표하는 변수 중에서 구조물 고유감쇠의 영향이 가장 두드러지는 것으로 나타났다.

• 콘크리트학회지
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• 제10권6호
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• pp.149-159
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• 1998

프리스트레스트 콘크리트 박스 거더 교량의 장기거동의 정확한 예측은 시공중 및 완공후의 사용성 확보를 위해서 매우 중요하다. 이러한 장기거동은 콘크리트의 크리프와 건조수축등의 확률특성에 따라 크게 영향을 받는다. 따라서, 본 논문에서는 프리스트레스트 콘크리트 박스거더 교량에서의 크리프와 건조수축효과의 불확실성 및 민감도 해석에 관한 연구를 수행하였다. 콘크리트의 크리프와 건조수축효과의 불확실성은 입력이자의 변동성을 고려하여 산출한다. 불확실성 및 민감도 해석은 Latin Hypercube 샘플링 기법에 의해 수행하며, 각 샘플에 대하여 시간 의존적 구조해석을 하여 그 결과를 통계학적으로 분석한다. 본 연구에서는 각 입력인자의 구조해석 결과에 대한 민감도를 정량화 하기 위하여 3가지 즉, RCC, PRCC 와 SRCC 상관계수를 사용하여 민감도 해석을 수행하였다. 현재, 주로 교량설계시 사용되는 ACI모델, CEB-FIP모델과 도로교 표준시방서 모델의 민감도 분석을 수행한결과 크리프 모델 자체의 불확실성과 상대습도가 시간에 따른 변형에 가장 중요한 영향인자인 것으로 나타났다. 본 연구에서는 장기거동에 영향을 미치는 주요인자를 도출하는 합리적인 해석기법을 정립하였으며, 이로부터 좀 더 합리적인 모델정립에 유용한 토대가 될 것으로 사료된다.

• Nuclear Engineering and Technology
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• 제21권1호
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• pp.18-31
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• 1989

대기오염의 제어가 발전 단가에 미치는 영향을 분석하기 위하여 전산 모델이 개발 되었다. POGEN은 석탄 화력 발전소에 대해 대기오염 제어 비용을 가산한 균등화 발전 단가를 계산한다. 부 프로그램 Pollution은 대기 오염 제어 비용을 가산한 지배 방정식을 사용하여 총 자본 비용과 변동비용을 계산한다. 이 비용은 균등화 발전 단가를 계산하는 부 프로그램 GENeration의 추가 입력으로 사용된다. 탈황설비의 직접 비용에 대한 Pollution을 이용한 결과는 경험이 풍부한 선진국에서 발간된 비용 자료로써 검증하였다. 2001년의 전력 생산비용은 석탄화력발전소에 적용된 세 가지의 규제 시나리오에 의해 추정되었다. 입력 변수의 중요도와 미래 발전소에 대한 입력 변수에 포함된 불확실성 때문에 생기는 불확실도의 전파를 검토하기 위해 Latin Hypercube Sampling과 Multiple Least Squares 방법을 사용하여 민감도 분석과 불확실도 분석을 수행하였다. 가장 민감한 입력 변수는 원자력, 화력 공히 할인률이다. 배출가스제어 비용으로서 9-11 mills/kWh 정도가 추가되어야 한다. 이 비용은 전력 생산비용의 거의 20 퍼센트가 되고, 이에 해당하는 투자비는 1GW 용량의 석탄 화력발전소 초기 투자비용의 40%가 될 것이다. 원자력 발전에 대한 단가는 90퍼센트의 신뢰도로써 32.6-65.9, 석탄 화력에 대해서는 45.5-60.5 mills/kWh가 되며, 엄격한 규제 분위기 하에서는 원자력이 95%의 신뢰도로써 유리할 것이 전망된다.

• International Journal of Fluid Machinery and Systems
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• 제3권2호
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• pp.150-159
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• 2010

Laidback fan shaped film-cooling hole is formulated numerically and optimized with the help of three-dimensional numerical analysis, surrogate methods, and the multi-objective evolutionary algorithm. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by four geometric design variables, the injection angle of the hole, the lateral expansion angle of the diffuser, the forward expansion angle of the hole, and the ratio of the length to the diameter of the hole, to maximize the film-cooling effectiveness compromising with the aerodynamic loss. The objective function values are numerically evaluated through Reynolds- averaged Navier-Stokes analysis at the designs that are selected through the Latin hypercube sampling method. Using these numerical simulation results, the Response Surface Approximation model are constructed for each objective function and a hybrid multi-objective evolutionary algorithm is applied to obtain the Pareto optimal front. The clustered points from Pareto optimal front were evaluated by flow analysis. These designs give enhanced objective function values in comparison with the experimental designs.

• 대한기계학회논문집B
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• 제31권8호
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• pp.663-671
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• 2007

In this work, shape optimization of a wire-wrapped fuel assembly in a liquid metal reactor has been carried out by combining a three-dimensional Reynolds-averaged Navier-Stokes analysis with the radial basis neural network method, a well known surrogate modeling technique for optimization. Sequential Quadratic Programming is used to search the optimal point from the constructed surrogate. Two geometric design variables are selected for the optimization and design space is sampled using Latin Hypercube Sampling. The optimization problem has been defined as a maximization of the objective function, which is as a linear combination of heat transfer and friction loss related terms with a weighing factor. The objective function value is more sensitive to the ratio of the wire spacer diameter to the fuel rod diameter than to the ratio of the wire wrap pitch to the fuel rod diameter. The optimal values of the design variables are obtained by varying the weighting factor.

• International Journal of Fluid Machinery and Systems
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• 제9권3호
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• pp.265-276
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• 2016

Energy systems working coherently in different conditions may not have a specific design which can provide optimal performance. A system working for a longer period at lower efficiency implies higher energy consumption. In this effort, a methodology demonstrated by a jet pump design and optimization via numerical modeling for fluid dynamics and implementation of an evolutionary algorithm for the optimization shows a reduction in computational costs. The jet pump inherently has a low efficiency because of improper mixing of primary and secondary fluids, and multiple momentum and energy transfer phenomena associated with it. The high fidelity solutions were obtained through a validated numerical model to construct an approximate function through surrogate analysis. Pareto-optimal solutions for two objective functions, i.e., secondary fluid pressure head and primary fluid pressure-drop, were generated through a multi-objective genetic algorithm. For the jet pump geometry, a design space of several design variables was discretized using the Latin hypercube sampling method for the optimization. The performance analysis of the surrogate models shows that the combined surrogates perform better than a single surrogate and the optimized jet pump shows a higher performance. The approach can be implemented in other energy systems to find a better design.

• 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.

• 한국농공학회논문집
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• 제54권3호
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• pp.55-63
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• 2012

Soil properties are not random values which is represented by mean and standard deviation but show spatial correlation. Especially, soils are highly variable in their properties and rarely homogeneous. Thus, the accuracy and reliability of probabilistic analysis results is decreased when using only one random variable as design parameter. In this paper, to consider spatial variability of soil property, one-dimensional random fields of coefficient of consolidation ($C_v$) were generated based on a Karhunen-Loeve expansion. A Latin hypercube Monte Calro simulation coupled with finite difference method for Terzaghi's one dimensional consolidation theory was then used to probabilistic analysis. The results show that the failure probability is smaller when consider spatial variability of $C_v$ than not considered and the failure probability increased when the autocorrelation distance increased. Thus, the uncertainty of soil can be overestimated when spatial variability of soil property is not considered, and therefore, to perform a more accurate probabilistic analysis, spatial variability of soil property needed to be considered.