• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1307-1312
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• 2007

This paper proposes an optimal design scheme to reduce the noise of the engine cooling fan by adapting Kriging with two meta-heuristic techniques. An engineering model has been developed for the prediction of the noise spectrum of the engine cooling fan. The noise of the fan is expressed as the discrete frequency noise peaks at the BPF and its harmonics and line spectrum at the broad band by noise generation mechanisms. The object of this paper is to find the Optimal Design for Noise Reduction of the Engine Cooling Fan. We firstly show a comparison of the measured and calculated noise spectra of the fan for the validation of the noise prediction program. Orthogonal array is applied as design of experiments because it is suitable for Kriging. With these simulated data, we can estimate a correlation parameter of Kriging by solving the nonlinear problem with genetic algorithm and find an optimal level for the noise reduction of the cooling fan by optimizing Kriging estimates with simulated annealing. We notice that this optimal design scheme gives noticeable results. Therefore, an optimal design for the cooling fan is proposed by reducing the noise of its system.

• Journal of Species Research
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• v.9 no.4
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• pp.325-338
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• 2020

The animal gut is filled with highly diverse microbes associated with host metabolism, physiology, and pathology. However, numerous animal gut microbes have not been cultured or reported. We isolated various bacterial species using culture-dependent approaches during a comprehensive investigation of endangered endemic vertebrate species in the Republic of Korea. A total of 18 unrecorded bacterial species were isolated from the feces of an Oriental stork (Ciconia boyciana), and from the intestinal tracts of a cobitid fish (Kichulchoia multifasciata) and a Korean splendid dace (Coreoleuciscus splendidus). Based on a phylogenetic analysis of 16S rRNA gene sequences, we discovered species belonging to the phyla Actinobacteria (eight species), Firmicutes (seven species), Proteobacteria (two species), and Bacteroidetes (one species). Based on their high 16S rRNA gene sequence similarities (>98.7%) and formation of monophyletic clades with type species, each species was classified into an independent and predefined bacterial species. Gram-stain reaction, colony and cell morphology, basic biochemical characteristics, isolation source, and NIBR IDs for each species are described in the species description section.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.622-626
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• 1993

비원형기어의 기본적인 특징을 몇 가지 소개하고자 한다. 첫째, 간소한 기구로서 소형화할 수 있고, 둘째, 임의의 부동속 회전 전달을 얻을 수 있으며, 셋째, 맞물린 치면의 미끄럼접촉이 적기 때문에 마모피로가 적고 넷째, 고부하 전달이 가능하다는 장점들이 있다. 본 연구의 목적은 링크, 캠과 같은 동일한 용도에서 사용되는 다른 여러 기구에 비해 많은 이점을 가지고 있는 적합한 타원계 비원형기어(엽형)에서 편평도의 변화에 따른 피치라인을설계하고, 각속비 및 편평도에 따른 형상과 길이의 변화, 물림압력각, 곡률반경등의 연구를 바탕으로 스퍼형과 헬리컬형의 타원계 엽형로타를 AOTOCAD의 script, 3dace를 이용하여 Computer Simulation를 통해 도형화한다.

• Proceedings of the Korean Society of Veterinary Pathology Conference
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• 2005.11a
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• pp.83.1-84
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• 2005

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.289-295
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• 2005

LMTT (Linear Motor-based Transfer Techn-ology) is a horizontal transfer system for the yard automation This system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) toot consists of stator modules on the rail and shuttle car. In this research, the kriging interpolation method with sequential sampling find the optimum design of mover in LMTT. The design variables are considered as the transverse, longitudinal and wheel beam's thicknesses. The objective function is set up as weight, while the constant function are set up as the stresses generated by four loading conditions. The objective function is set up as weight. The optimum results obtained by the suggested method are compared with those by the GENESIS.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.339-344
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• 2001

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM (Finite Element Method) and BEM (Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta-modeling technique has been developed for solving such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building meta-models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty-six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.941-948
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• 2006

In this study, the new method for reliability estimation is proposed using kriging metamodel. Kriging metamodel can be determined by appropriate sampling range and sampling numbers because there are no random errors in the Design and Analysis of Computer Experiments(DACE) model. The first kriging metamodel is made based on widely ranged sampling points. The Advanced First Order Reliability Method(AFORM) is applied to the first kriging metamodel to estimate the reliability approximately. Then, the second kriging metamodel is constructed using additional sampling points with updated sampling range. The Monte-Carlo Simulation(MCS) is applied to the second kriging metamodel to evaluate the reliability. The proposed method is applied to numerical examples and the results are almost equal to the reference reliability.

• Journal of Korean Society for Quality Management
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• v.34 no.2
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• pp.122-128
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• 2006

One feature of a computer simulation experiment, different from a physical experiment, is that the output is often deterministic. Moreover the codes are computationally very expensive to run. This paper deals with the design and analysis of computer experiments(DACE) which is a relatively new statistical research area. We model the response of computer experiments as the realization of a stochastic process. This approach is basically the same as using a spatial linear model. Applications to the optimal mechanical designing and model calibration problems are illustrated. Algorithms for selecting the best spatial linear model are also proposed.

• Korean Journal of Veterinary Service
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• v.29 no.4
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• pp.503-506
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• 2006

Cyclopia is a congenital ocular abnormality in which two orbits are fused together due to an arrest in the normal process of embryonic tissue development. Reported here is a case of cyclopia in a calf observed from the uterus of cow slaughtered in an abattoir in Korea on March 24, 2004. The calf possessed a spherical-shaped head and only one centrally placed eye. The one eyeball showed complete eyelashes on the defective eyelids. The nasal region and the anterior nares were absent along with a dorsally curved mandible extended beyond the defective maxillae.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.277-283
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• 2005

Kriging model is widely used as design analysis and computer experiment (DACE) model in the field of engineering design to accomplish computationally feasible design optimization. In general, kriging model has been applied to many engineering applications as an interpolation model because it is usually constructed from deterministic simulation responses. However, when the responses include not only global nonlinearity but also numerical error, it is not suitable to use Kriging model that can distort global behavior. In this research, generalized kriging model that can represent both interpolation and regression is proposed. The performances of generalized kriging model are compared with those of interpolating kriging model for numerical function with error of normal distribution type and trigonometric function type. As an application of the proposed approach, the response of a simple dynamic model with numerical integration error is predicted based on sampling data. It is verified that the generalized kriging model can predict a noisy response without distortion of its global behavior. In addition, the influences of maximum likelihood estimation to prediction performance are discussed for the dynamic model.