• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2009년 추계학술대회논문집
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• pp.71-76
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• 2009

The research to predict the resistance performance of the ship using the CFD analysis is increasing. For the CFD numerical analysis the computational mesh, which is proper to computational model, has to be made before the analysis is begun. In the parametric study, even though the deformation of each case is not very sharp, the whole computational mesh should be regenerated according to the conventional way. Hence, lots of effort is needed to repeated mesh generation work. To solve these problems, the automatic mesh generation method using the macro function of commercial CAD program and mesh generation program is introduced in this study. First, in the CAD program, by using the macro function and putting the deformation rate of bow and stern in lengthwise, the repeated modeling work is performed automatically. Next, the generated geometries are read by the mesh generation program and the proper mesh for the geometry is created automatically also using the macro function. The hybrid mesh which has unstructured grid near the bow and stern and structured grid in the remaining part of domain is used. The verification of the developed method is done by applying the method to predict the resistance performance of the podded propulsion cruise ship of the Daewoo Shipbuilding & Marine Engineering (DSME) in the cases of different length of bow and stern and pod set in different position. The author believes that the introduced method can help to make the database to optimize the resistance performance of the ship in various cases can be constructed without difficulty.

• 시스템엔지니어링워크숍
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• 통권4호
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• pp.182-187
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• 2004

Our research proposes how to, systematically, count function point from initial functional requirements based on natural language. Gradually, Function Point Analysis is used to overcome the limitation of LOC(Line Of Code) for estimating software size. Moreover, it plays an important role in cost management. Function point is derived from initial requirements and is determined by experts who have an education for function point. However, currently there are few researches to cout function point by systematic or automatic rules. Through extending our porposed method, we expect that function point is able to be counted automatically or semi-automatically. This would be our future research

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1244-1244
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from mastitic and healthy cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from mastitic and healthy cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA and FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference, thereby providing a useful means for spectroscopy-based clinic applications.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1042-1042
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.

• 전기학회논문지
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• 제58권9호
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• pp.1790-1795
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• 2009

For GPR(Ground Penetrating Radar) applications, an accurate analysis of the scattered field is necessary to identify the unknown target. Dyadic Green's function of the multilayered medium is developed and applied to analysis of the underground conducting object. We used method of moment(MOM) with dyadic Green's function, and Discrete Complex Image Method(DCIM). To reduce the computational complexity, fast multipole method is introduced and we showed the accuracy of the method comparing with the conventional method of moment. For investigating the underground conducting target, several numerical experiments were accomplished using this method.

• Geomechanics and Engineering
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• 제9권3호
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• pp.313-328
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• 2015

In the present study, a CPT-based p-y analysis method was proposed for offshore mono-piles embedded in sands. Static and cyclic loading conditions were both taken into account for the proposed method. The continuous soil profiling capability of CPT was an important consideration for the proposed method, where detailed soil profile condition with depth can be readily incorporated into the analysis. The hyperbolic function was adopted to describe the non-linear p-y curves. For the proposed hyperbolic p-y relationship, the ultimate lateral soil resistance $p_u$ was given as a function of the cone resistance, which is directly introduced into the analysis as an input data. For cyclic loading condition, two different cyclic modification factors were considered and compared. Case examples were selected to check the validity of the proposed CPT-based method. Calculated lateral displacements and bending moments from the proposed method were in good agreement with measured results for lateral displacement and bending moment profiles. It was observed the accuracy of calculated results for the conventional approach was largely dependent on the selection of friction angle that is to be adopted into the analysis.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2009년도 정보통신설비 학술대회
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• pp.45-48
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• 2009

In this paper, we use the optimization design theory based on the finite element method and implement the optimal design of electromagnetic devices using COMSOL interface. COMSOL is one of the commercial EM software. Shape information for the design optimization is extracted by CAD in EM software. To calculate the shape of optimal design, sensitive analysis is applied to the design processing in MATLAB. To achieve the design objective in this paper, objective function is defined. According to the sensitive analysis based on the finite element method, we change the design variable after the sensitivity of the objective function is computed. To verify the proposed method, the results are compared with the initial design.

• 대한조선학회논문집
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• 제41권1호
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• pp.1-7
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• 2004

GUI program for analyzing directional spectrum waves is introduced in this paper Basically, MLM (Maximum Likelihood Method) was used for this program which was additionally consisted of performing spectral and time domain analysis for two dimensional irregular waves. Moreover, the directionality of directional spectrum waves generated by single summation and double summation method was investigated based on MLM. The directionality from each summation method has good agreement compared with that of target wave spreading function in the case of single wide directional spectrum waves. In addition to this, the resolution of directionality in double summation method was investigated as introducing coherence function between each wave component

• 한국자동차공학회논문집
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• 제3권5호
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• pp.10-16
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• 1995

In this study, the optimum design is carried out upon the crankshaft of in-line 6-cylinder internal combustion diesel engine with the mechanical analysis for the layout design, which is standard calculation whose process contains quadratic curve fitting method and quasi newton method about cost function, design variables and constraint conditions, Without finite element analysis, this process in wich mechanical analysis is performed upon the most critical part in crankshaft gives necessary and satisfied output in layout design and saves time and cost in developing a new diesel engine. In this study, also, the 3-dimensional finite element method is used in confirming the standard calculation for the optimization of crankshaft and the shape optimization in crankweb is obtained.

• Journal of Magnetics
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• 제16권1호
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• pp.77-82
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• 2011

This paper presents a new self-adjoint material sensitivity formulation for optimal designs and inverse problems in the high frequency domain. The proposed method is based on the continuum approach using the augmented Lagrangian method. Using the self-adjoint formulation, there is no need to solve the adjoint system additionally when the goal function is a function of the S-parameter. In addition, the algorithm is more general than most previous approaches because it is independent of specific analysis methods or gridding techniques, thereby enabling the use of commercial EM simulators and various custom solvers. For verification, the method was applied to the several numerical examples of dielectric material reconstruction problems in the high frequency domain, and the results were compared with those calculated using the conventional method.