• Proceedings of the KSME Conference
• /
• 2004.04a
• /
• pp.1017-1022
• /
• 2004

Though the standard element density-based topology optimization method has been applied for the optimal design of multiphysics systems, some theoretical problems, such as material interpolation, undershoot temperature prediction, and unstable elements, still remain to be overcome. The objective of this investigation is to present a new topology optimization formulation based on the element connectivity parameterization (ECP) in order to avoid the numerical problems in multiphysics system design and improve optimization results. To show the validity of the proposed approach, the designs of an optimal thermal dissipation and an electro-thermal-compliant actuator were considered.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.11a
• /
• pp.475-478
• /
• 2005

Calculation of wear depth with regard to the wear topology is peformed numerically Four typical wear topology, that is round, crescent, flat, and diamond types are adopted to represent the configuration of wear volume. Diamond and flat types are the most severe topology for wear depth history, whereas round and crescent types have small increasing rate of wear depth to the wear volume. Based on this study we can guess that the most severe wear phenomena happens to be upper side of U-tubes in the KSNP SG, because flat or diamond wear will be generated by the wearing motion between tubes and diagonal, vertical, horizontal strips. The misalignment of tube at the stage of manufacturing or distortion of upper structure due to the thermal expansion or vibration of upper structure such as diagonal, vertical, and horizontal strips will be one of the main causes of flat or diamond wear.

• Journal of Intelligence and Information Systems
• /
• v.16 no.3
• /
• pp.1-14
• /
• 2010

The back-propagation neural network (BPN) has long been successfully applied in bankruptcy prediction problems. Despite its wide application, some major issues must be considered before its use, such as the network topology, learning parameters and normalization methods for the input and output vectors. Previous studies on bankruptcy prediction with BPN have shown that many researchers are interested in how to optimize the network topology and learning parameters to improve the prediction performance. In many cases, however, the benefits of data normalization are often overlooked. In this study, a genetic algorithm (GA)-based normalization transform, which is defined as a linearly weighted combination of several different normalization transforms, will be proposed. GA is used to extract the optimal weight for the generalization. From the results of an experiment, the proposed method was evaluated and compared with other methods to demonstrate the advantage of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.6 no.2
• /
• pp.13-21
• /
• 1996

The necessity and usefulness of higher-order neural networks have been well-known since early days of neurocomputing. However the explosive number of terms has hampered the design and training of such networks. In this paper we present an evolutionary learning method for efficiently constructing problem-specific higher-order neural models. The crux of the method is the neural tree representation employing both sigma and pi units, in combination with the use of an MDL-based fitness function for learning minimal models. We provide experimental results in classification and prediction problems which demonstrate the effectiveness of the method. I. Introduction topology employs one hidden layer with full connectivity between neighboring layers. This structure has One of the most popular neural network models been very successful for many applications. However, used for supervised learning applications has been the they have some weaknesses. For instance, the fully mutilayer feedforward network. A commonly adopted connected structure is not necessarily a good topology unless the task contains a good predictor for the full *d*dWs %BH%W* input space.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.19 no.12
• /
• pp.1356-1363
• /
• 2009

The aim of this research is to construct eigenfrequency optimization codes for plates with Arbitrary Rank Microstructures. From among noise factors, resonance sound is main reason for floor's solid noise. But, Resonance-elusion design codes are not fixed so far. Besides, The prediction of composite material's capability and an resonance elusion by controlling natural frequency of plate depend on designer's experiences. In this paper, First, using computer program with arbitrary rank microstructure, variation on composite material properties is studied, and then natural frequency control is performed by plate topology optimization method. The results of this study are as followed. 1) Programs that calculate material properties along it's microstructure composition and control natural frequency on composite material plate are coded by Homogenization and Topology Optimization method. and it is examined by example problem. 2) Equivalent material properties, calculated by program, are examined for natural frequency. In this paper, Suggested programs are coded using $Matlab^{TM}$, Feapmax and Feap Library with Homogenization and Topology Optimization method. and Adequacy of them is reviewed by performing the maximization or minimization of natural frequency for plates with isotropic or anisotropic materials. Since the programs has been designed for widely use. If the mechanism between composite material and other structural member is identified, extension application may be possible in field of structure maintenance, reinforcement etc. through application of composite material.

• Journal of Ship and Ocean Technology
• /
• v.5 no.2
• /
• pp.27-48
• /
• 2001

Turbulent flow calculations are performed for the two modern practical VLCCs with the sable forebody and the slightly different afterbody, i.e. KVLCC and KVLCC2. Three $\textsc{k}-\varepsilon$ turbulence models are tested to investigate the differences caused by the turbulence models. The calculated results around the two VLCC hull forms using O-O grid topology and profile-fitted surface meshes are compared to the measured data from towing tank experiment. The realizable $\textsc{k}-\varepsilon$model provided realistic wake distribution with hook-like shape, while the standard and RNG-based $\textsc{k}-\varepsilon$models failed. It is very encouraging to see that the CFD with relatively simple turbulence closure can tell the difference quantitatively as well as qualitatively for the two hull forms with stern frameline modification.

• Proceedings of the KIEE Conference
• /
• 1994.07a
• /
• pp.459-461
• /
• 1994

This paper proposed a new converter topology improving the split source type converter. In this converter. two switches and six diodes add to the split source type converter. The proposed converter has a performance minimized a negative torqe, putting a phase current off by double impressed voltage 2Vdc. Hence, a new converter results in increase of the average output power and improves converter efficiency in heavy load and high speed. Theoretical prediction is verified by experimental results got with a new proposed converter and 8/6 poles SRM.

• Journal of information and communication convergence engineering
• /
• v.6 no.4
• /
• pp.383-390
• /
• 2008

Clock skew modeling is important in the performance evaluation and prediction of clock distribution network and it is one of the major constraints for high-speed operation of synchronous integrated circuits. In clock routing synthesis, it is necessary to reduce the clock skew under the specified skew bound, while minimizing the cost such as total wire length and delay. In this paper, a new efficient bounded clock skew routing method is described, which generalizes the well-known bounded skew tree method by allowing loops, i.e., link-edges can be inserted to a clock tree when they are beneficial to reduce the clock skew and/or the wire length. Furthermore, routing topology construction and wire sizing is used to reduce clock delay.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2004.10a
• /
• pp.13-18
• /
• 2004

In this study, a new method is proposed generating 3D wire-frames of building using the lowest level topology, points, which are input by human operators. Through the procedure, it is possible to make prediction occlusion points and generate the topology automatically among points, lines, surfaces from buildings. In order to adjust the error of initial values which are input manually, the least squares adjustment for model-image fitting is carried out using the edge information of aerial imagery. And also, model fitting procedure is done making all surfaces plane of buildings by the least squares adjustment. As a result of those procedure, 3D building models are refined similar to real figures of buildings.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.6B
• /
• pp.534-543
• /
• 2006

As the topology frequently varies, more cluster reconstructing is needed and also management overheads increase in the wireless ad hoc/sensor networks. In this paper, we propose a multi-hop clustering algorithm for wireless sensor network topology management using dynamic pre-clusterhead scheme to solve cluster reconstruction and load balancing problems. The proposed scheme uses weight map that is composed with power level and mobility, to choose pre-clusterhead and construct multi-hop cluster. A clusterhead has a weight map and threshold to hand over functions of clusterhead to pre-clusterhead. As a result of simulation, our algorithm can reduce overheads and provide more load balancing well. Moreover, our scheme can maintain the proper number of clusters and cluster members regardless of topology changes.