• Water for future
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• v.29 no.3
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• pp.177-186
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• 1996

QUAL2E model was applied to assess the water quality variations due to dredging of the bottom deposit in the downstream of the Nakdong River. A variedflow analysis was performed for the reach of Namji to Nakdong Estuary to estimate the hydraulic parameters. BFGS (Broyden-Fletcher-Goldfarb-Shanno) method was applied to determine the optimum reaction parameters and model verrification was performed based on these. Water quality modeling of dredging effects for BOD and DO in the reach was performed under low and average flow conditions and alternatives. It revealed that dredging had significant effedcts on the improvement of water quality in the reach.

• Journal of computational fluids engineering
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• v.6 no.2
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• pp.9-21
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• 2001

초음속 여객기의 천음속 순항 성능을 개선하기 위하여 날개의 플랩 꺽임각을 최적화하였다. 이를 위하여 3차원 Euler 코드와 adjoint 코드를 이용한 최적설계기법을 적용하였다. 설계변수로서, 앞전플랩 5개, 뒷전 플랩 5개 등 총 10개의 플랩의 꺽임각이 사용되었다. 설계과정중에 격자계 내부격자점의 수정을 위해 타원형방정식법을 이용하였다. 계산 시간의 단축을 위해 내부격자의 민감도는 무시하였다. 또한 본 설계문제에 근사구배기법의 적용가능성 여부를 조사하였다. 충격파가 없는 경우 앞전 플렙에 한하여 근사구배기법을 적용할 수 있음을 알았다. 최적설계기법으로 BFGS기법을 적용하여 항력을 최소화하였으며, 양력 및 날개 표면 마하수에 대한 제약조건을 적용하였다. 앞전 플랩의 최적화 및 앞전과 뒷전 플랩의 최적화 등 두 개의 설계 문제를 고려하였다. 성공적인 결과를 얻음으로써 본 설계방법의 타당성 및 효율성을 확인하였다.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.195-209
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• 2003

Spatial-Stochastic Neural Networks Model(SSNNM) is used to estimate long-term streamflow in the parallel reservoir groups. SSNNM employs two kinds of backpropagation algorithms, based on LMBP and BFGS-QNBP separately. SSNNM has three layers, input, hidden, and output layer, in the structure and network configuration consists of 8-8-2 nodes one by one. Nodes in input layer are composed of streamflow, precipitation, pan evaporation, and temperature with the monthly average values collected from Andong and Imha reservoir. But some temporal differences apparently exist in their time series. For the SSNNM training procedure, the training sets in input layer are generated by the PARMA(1,1) stochastic model and they covers insufficient time series. Generated data series are used to train SSNNM and the model parameters, optimal connection weights and biases, are estimated during training procedure. They are applied to evaluate model validation using observed data sets. In this study, the new approaches give outstanding results by the comparison of statistical analysis and hydrographs in the model validation. SSNNM will help to manage and control water distribution and give basic data to develop long-term coupled operation system in parallel reservoir groups of the Upper Nakdong River.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.163-171
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• 2024

This study applies neural network analysis techniques to examine the factors influencing the purchasing decisions of fashion eyewear among women in their 30s and 40s, comparing these findings with traditional parametric analysis methods. In the fashion area, machine learning techniques are utilized for personalized fashion recommendation systems. However, research on such applications in Korea remains insufficient. By reanalyzing a study conducted in 2017 using traditional quantitative methods with these new techniques, this study aims to confirm the utility of neural network methods. Notably, the study finds that the classification accuracy of preferred sunglasses design is highest, at 86.2%, when the L-BFGS-B neural network is activated using the hyperbolic tangent function. The most critical factors influencing purchasing decisions were consumers' occupations and their pursuit of new styles. It is interpreted that Korean sunglasses consumers prefer "safe changes." These findings are consistent for selecting both the frames and lenses of sunglasses. Traditional quantitative analysis suggests that the type of sunglasses preferred varies according to the group to which a consumer belongs. In contrast, neural network analysis predicts the preferred sunglasses for each individual, thereby facilitating the development of personalized sunglasses recommendation systems.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.10
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• pp.1335-1342
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• 2000

Three-dimensional flow analysis and numerical optimization methods are presented for the design of an axial-flow fan. Steady, incompressible, three-dimensional Reynolds-averaged Navier-Stokes equations are used as governing equations, and standard k- ${\varepsilon}$ turbulence model is chosen as a turbulence model. Governing equations are discretized using finite volume method. Steepest descent method, conjugate gradient method and BFGS method are compared to determine the searching directions. Golden section method and quadratic fit-sectioning method are tested for one dimensional search. Objective function is defined as a ratio of generation rate of the turbulent kinetic energy to pressure head. Two variables concerning sweep angle distribution are selected as the design variables. Performance of the final fan designed by the optimization was tested experimentally.

• 유체기계공업학회:학술대회논문집
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• 1999.12a
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• pp.221-226
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• 1999

Three-dimensional flow analysis and numerical optimization methods are presented for the design of an axial-flow fan. Steady, Incompressible, three-dimensional Reynolds-averaged Wavier-Stokes equations are used as governing equations, and standard k-$\epsilon$ turbulence model is chosen as a turbulence model. Governing equations are discretized using finite volume method. Steepest descent method, conjugate gradient method and BFGS method are compared to determine the searching directions. Golden section method and quadratic fit-sectioning method are tested for one dimensional search. Objective function is defined as a ratio of generation rate of the turbulent kinetic energy to pressure head. Sweep angle distributions are used as design variables.

• Journal of Korea Water Resources Association
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• v.35 no.4 s.129
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• pp.385-395
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• 2002

A stochastic model using FOEA(First-Order Error-Analysis) and Monte Carlo Method is developed to predict water quality variation in a river. A sensitivity analysis using influential matrix is performed to determine the significant reaction coefficients. Also the BFGS (Broyden-Fletcher-Goldfarb-Shanno) optimization method is applied to estimate the optimal values of the major reaction coefficients. The developed stochastic model is applied to the real study reach and the results are agreed well with those of deterministic analysis. The process for analyzing the uncertainties of the discharge, water quality and reaction coefficients of headwater and tributaries is included in the model to estimate the influence on the water quality variation at downstream. The extents of contribution of the uncertainties influencing on the total uncertainty can be evaluated from the results of the model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4C
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• pp.229-238
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• 2006

Observed field behaviors are frequently different from the behaviors predicted in the design state due to several uncertainties involved in soil properties, numerical modeling, and error of measuring system even though a sophisticated numerical analysis technique is applied to solve the consolidation behavior of drainage-installed soft deposits. In this study, genetic algorithms are applied to back-analyze the soil properties using the observed behavior of soft clay deposit composed of multi layers that shows complex consolidation characteristics. Utilizing the program, one might be able to appropriately predict the subsequent consolidation behavior from the measured data in an early stage of consolidation of multi layered soft deposits. Example analyses for drainage-installed multi-layered soft deposits are performed to examine the applicability of proposed back-analysis method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.1 s.173
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• pp.190-195
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• 2000

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure. Nikolakopoulos et. al. used the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However the intersecting point of the superposed contours is not only difficult to find but also incorrect to calculate. A method is presented in this paper which uses optimization technique for the location and depth of the crack. The basic idea is to find parameters which use the structural eigenfrequencies on crack depth and location and optimization algorithm. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. Method of optimization is augmented lagrange multiplier method and search direction method is BFGS variable metric method and one dimensional search method is polynomial interpolation.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.974-982
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• 2009

To improve the effectiveness and economics the bridge design methodology considering the bridge/rail longitudinal analysis and bridge/vehicle dynamic effect suggested in this study. The reliability-based Life-Cycle Costs(LCC) effective optimum design is applied to a 2-main steel girder bridge, 5$\times$(1@50m) for comparison with conventional design, initial cost optimization and equivalent LCC optimization. As a result of the optimum design based on reliability, it may be stated that the design of High-Speed railway bridges considering the bridge/rail longitudinal analysis and bridge/vehicle dynamic effect are more efficient than typical existing bridges and LCC optimization without respect to bridge/rail longitudinal analysis and bridge/vehicle dynamic effect. The result of optimization design considering the interaction, design methodology suggested in this study, is higher than result of initial cost optimization design in initial cost, but that has the advantage than result of initial cost optimization design in expected LCC.