• 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.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.3 no.1
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• pp.55-62
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• 1996

MRNS network is a general algebraic structure of Hypercube network which has recently drawn considerable attention to supercomputing and message-passing communication. In this paper, we investigate the routing of a message in an n- dimensional MRNS network that is a key to the performance of this network. On the n-dimensional MRNS network we would like to transmit packets from a source node to a destination node simultaneously along a fixed number of paths, where the superscript packet will traverse along the superscript path. In order for all packets to arrive at the destination node quickly and securely, the ith path must be node-disjoint from all other paths. By investigating the conditions of node-disjoint paths, we will employ the special matrices called as the Hamiltonian Circuit Latin Square(HCLS) described in 〔1〕to construct a set of node-disjoint paths and suggest a linear-time parallel routing algorithm for the MRNS network.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.151-157
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• 1998

Free-space optical interconnection networks can be classified into two types, space variant and space invariant, according to the degree of space variance. In terms of physical implementations, the degree of space variance can be interpreted as the degree of sharing beam steering optics among the nodes of a given network. This implies that all nodes in a totally space-invariant network can share a single beam steering optics to realize the given network topology, whereas, in a totally space variant network, each node requires a distinct beam steering optics. However, space invariant networks require mechanisms for distinguishing the origins of incoming signals detected at the node since several signals may arrive at the same time if the node degree of the network is greater than one. This paper presents a signal source encoding scheme for distinguishing incoming signals efficiently, in terms of the number of detectors at each node or the number of unique wavelengths. The proposed scheme is solved by developing a new parallel genetic algorithm called distributed asynchronous genetic algorithm (DAGA). Using the DAGA, we solved signal distinction schemes for various network sizes of several topologies such as hypercube, the mesh, and the de Brujin.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.499-506
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• 2005

Recently, Hyper-Star network HS(m,k) which improves the network cost of hypercube has been proposed. In this paper, we show that the bisection width of regular Hyper-Star network HS(2n,n) is maximum (2n-2,n-1). Using the concept of container, we also show that k-wide diameter of HS(2n,n) is less than dist(u,v)+4, and the fault diameter is less than D(HS(2n,n))+2, where dist(u,v) is the shortest path length between any two nodes u and v in HS(2n,n), and D(HS(2n,n)) is its diameter.

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

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

• Annual Conference of KIPS
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• 2007.11a
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• pp.663-666
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• 2007

본 논문에서는 하이퍼큐브보다 망비용이 개선된 Folded 하이퍼큐브 연결망과 오드 연결망 사이의 임베딩을 분석한다. Folded 하이퍼큐브 $FQ_n$을 오드 연결망 $O_{2n+1}$에 연장율 2, 밀집율 1에 임베딩 가능함을 보이고, 오드 연결망 $O_d$을 Folded 하이퍼큐브 $FQ_{2d-1}$에 연장율 2, 밀집율 1에 임베딩 가능함을 보인다.

• Annual Conference of KIPS
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• 2007.11a
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• pp.667-670
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• 2007

알고리즘의 설계에 있어서 주어진 연결망을 다른 연결망으로 임베딩하는 것은 알고리즘을 활용하는 중용한 방법중의 하나이다. 본 논문에서는 하이퍼큐브보다 망비용이 개선된 이븐 연결망과 오드 연결망 사이의 임베딩을 분석하고, 이븐 연결망이 이분할 연결망임을 보인다. 이븐 연결망을 오드 연결망에 연장율 2, 밀집율 1에 임베딩 가능함을 보이고, 오드 연결망을 이븐 연결망에 연장율 2, 밀집율 1에 임베딩 가능함을 보인다.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.394-400
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• 2002

Networks of Workstations(NOWs), that has features of flexibility and scalability, recently has emerged as an inexpensive alternative to massively parallel multicomputers. However it is not easier to perform deadlock-free multicast than regular topologies like mash or hypercube. Single phase differential multicast(SPDM) is a modified multicast algorithm with less burden of the root node. By applying quality of serviece(QoS), a specific node can have differentiated service and artificial change of message flow pattern is also available. As the results of performance evaluation experiments, SPDM has lower latency and lower packet concentration rate of the root node than the case of SPAM, and has ability to control network load distribution among switch nodes by controlling the assignment rate among nodes.