• 한국전산유체공학회:학술대회논문집
• /
• 2011.05a
• /
• pp.100-103
• /
• 2011

In the present work, a numerical study of fluid flow and heat transfer on the concave surface with impinging jet has been performed by solving three-dimensional Reynods-averaged Naver-Stokes(RANS) equations. The constant temperature condition was applied to the concave impingement surface. The inclination angle of jet nozzle and the distance between jet nozzles are chosen as design variables under equivalent mass flow rate of working fluid into cooling channel, and area averaged Nusselt number on concave impingement surface is set as the objective function. Thirteen training points are obtained by Latin Hypercube sampling method, and the PEA model is constructed by using the objective function values at the trainging points. And, the sequential quadratic programming is used to search for the optimal paint from the PBA model. Through the optimization, the optimal shape shows improved heat transfer rate as compared to the reference geometry.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.32 no.4
• /
• pp.317-326
• /
• 2008

The main purpose of the present study is to perform shape optimizations of transonic compressor blade in order to enhance its performance. In this study, the Latin hypercube sampling of design of experiments and the weighted average surrogate model with the help of a gradient based optimization algorithm are used within design space by the lower and upper limits of each design variable and for finding optimum designs, respectively. 3-D Reynolds-averaged Navier-Stokes solver is used to evaluate the objective functions of adiabatic efficiency and pressure ratio. Six variables from lean and airfoil thickness profile are selected as design variables. The results show that the adiabatic efficiency is enhanced by 1.43% by efficiency optimization while the pressure ratio is increased very small, and pressure ratio is increased by 0.24% by pressure ratio optimization.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.1
• /
• pp.184-189
• /
• 2014

This paper presents a multi-objective optimization approach to design rotor slot geometry of three-phase squirrel cage induction machine to achieve NEMA design D torque-speed (T-S) characteristics with high efficiency. The multi-objective Particle Swarm Optimization (MOPSO) algorithm combined with the adaptive response surface method and Latin hypercube sampling strategy is applied to obtain the Pareto optimal designs. In order to demonstrate the validity of the suggested optimal algorithm, an application to rotor slot design of three-phase induction motor is presented.

• Korean Journal of Mathematics
• /
• v.5 no.1
• /
• pp.55-60
• /
• 1997

A continuum structure function(CSF) is a non-decreasing mapping from the unit hypercube to the unit interval. The reliability importance of component $i$ in a CSF at system level ${\alpha}$, $R_i({\alpha})$) say, is zero if and only if component $i$ is almost irrelevant to the system at level ${\alpha}$. A condition to check whether a component is almost irrelevant to the system is presented. It is shown that $R^{(m)}_i({\alpha}){\rightarrow}R_i({\alpha})$ uniformly as $m{\rightarrow}{\infty}$ where each $R^{(m)}_i({\alpha})$ is readily calculated.

• The KSFM Journal of Fluid Machinery
• /
• v.11 no.2
• /
• pp.46-54
• /
• 2008

This study presents a numerical optimization to optimize an axial flow fan blade to increase the efficiency. The radial basis neural network is used as an optimization method with the numerical analysis by Reynolds-averaged Navier-Stokes equations using SST model as turbulence closure. Four design variables related to airfoil maximum camber, maximum camber location, leading edge radius and trailing edge radius, respectively, are selected, and efficiency is considered as objective function which is to be maximized. Thirty designs are evaluated to get the objective function values of each design used to train the neural network. Optimum shape shows the efficiency increased by 1.0%.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.12
• /
• pp.102-109
• /
• 2009

This study proposes the structural optimization of a manifold valve. FE analysis is performed to evaluate the strength of a manifold valve. In addition, the structural optimization technique is applied to reduce its weight. In this study, the optimization method using the kriging interpolation method is adopted to obtain the minimum weight satisfying the strength constraint. The maximum stress and the weight are replaced by the metamodels. In this process, tile sample points are generated by latin-hypercube design. Optimum designs are obtained by ANSYS Workbench and the in-house program.

• Proceedings of the Korean Nuclear Society Conference
• /
• 1998.05a
• /
• pp.881-886
• /
• 1998

한국형 표준 원진(울진 원전 3,4호기)화해 사건에 대한 2 단계 확률론적 안전성평가 (Level 2PSA) 에서 격납건물 파손모드에 큰 영향을 준다고 판단되는 현상들에 대한 불확실성 분석을 수행하였다. 불확실성 분석 대상은 주로 민감도분석 및 기존 2단계 PSA수행결과 중요한 인자로 선정된 8가지 주요 현상들로 국한하였다. 수행 방법은 성층화 추출방식 (Latin Hypercube Sampling)으로부터 발생된 1000개의 표본을 사용하였고, 분석결과는 두가지 불확실성 측도로 제시하였으며, 사용된 코드는 2 단계 PSA 분석용 전산코드인 CONPAS 이다. 불확실성 관리측면에서. 제일 불확실성이 높은 격납건물 파손모드인 원자로 공동바닥관통의 불확실성 인자를 줄이기 위해서는 CR-EJECT 현상에 대한 불확실성 을 줄여야 할 것이다.

• The KSFM Journal of Fluid Machinery
• /
• v.12 no.4
• /
• pp.44-53
• /
• 2009

Numerical design optimization of a fan-shaped hole for film-cooling has been carried out to improve film-cooling effectiveness 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. The injection angle of hole, lateral expansion angle of hole and ratio of length-to-diameter of the hole are chosen as design variables and spatially averaged film-cooling effectiveness is considered as an objective function which is to be maximized. Twenty training points are obtained by Latin Hypercube sampling for three design variables. Sequential quadratic programming is used to search for the optimal point from the constructed surrogate. The film-cooling effectiveness has been successfully improved by the optimization with increased value of all design variables as compared to the reference geometry.

• Proceedings of the IEEK Conference
• /
• 2002.07c
• /
• pp.1371-1374
• /
• 2002

This paper compares four network con-figurations for using as the logical topology in multi- hop wavelength division multiplexing (WDM) networks. The regular network configurations studied in this paper axe ShuffleNet, de Bruijn graph, hypercube, and Man-hattan street network. Instead of using the weight mean hop distance of node placement problem for comparing optimum logical topology, we introduce a new objective function that includes h and the network cost. It can be seen that the network cost strongly depends on the logical topology selected for the implementation of the network. The objective of this paper is to find an optimum logical topology for WDM networks that gives low as well as low network cost.

• Korean Journal of Computational Design and Engineering
• /
• v.15 no.1
• /
• pp.24-32
• /
• 2010

This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.