• 대한기계학회논문집A
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• 제29권1호
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• pp.22-29
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• 2005

A material cloud method, which is a new topology optimization method, is presented. In MCM, an optimal structure can be found out by manipulating sizes and positions of material clouds, which are lumps of material with specified properties. A numerical analysis for a specific distribution of material clouds is carried out using fixed background finite element mesh. Optimal material distribution can be element-wisely extracted from material clouds' distribution. In MCM, an expansion-reduction procedure of design domain for finding out better optimal solution can be naturally realized. Also the convergence of material distribution is faster and well-defined material distribution with fewer intermediate densities can be obtained. In addition, the control of minimum-member sizes in the material distribution can be realized to some extent. In this paper, basic concept of MCM is introduced, and formulation and optimization results of MCM are compared with those of the traditional density distribution method(DDM).

• The Korean Journal of Ecology
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• 제21권5_1호
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• pp.409-418
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• 1998

A molel study was conducted to determine the optimal sample size for the analysis of the aquatic insect community in a stream reach of the Pangtae Creek, Kangwon-do in October 1995 and may 1996. The results showed that the required minimum sample size varied and depended on the purposes of the community analysis. Acoording to the Species: Area Curve method, at least 16 Surber samplings ($30{\times}30cm$) were required in a stream reach in each spring and fall survey. The species diversity index did not vary significantly as the sample size increased. Based on the coefficient of variation analysis, the minimum sample sizes of 10 were required in order to compare seasonal differences of the community in the study area. Considering the static community structure of aquatic insects, including both species numbers and individual numbers of aquatic insects, 11 and 7 samplings were optimal sizes for the fall and spring survey, respectively. We concluded that 12 Surber samplings from 3 riffle-pool sequences (4 samplings at each riffle-pool sequence) would be required in a stream reach (length 1 km) to obtain reliable as well as cost efficient data. Our model showed that the optimal sample size should be determined by interactions between minimum sample size, the degree of data reliability, and cost efficiency.

• Imaging Science in Dentistry
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• 제41권2호
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• pp.71-78
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• 2011

Purpose : This study was performed to determine the optimal tile size for the fractal dimension of the mandibular trabecular bone using a tile counting method. Materials and Methods : Digital intraoral radiographic images were obtained at the mandibular angle, molar, premolar, and incisor regions of 29 human dry mandibles. After preprocessing, the parameters representing morphometric characteristics of the trabecular bone were calculated. The fractal dimensions of the processed images were analyzed in various tile sizes by the tile counting method. Results : The optimal range of tile size was 0.132 mm to 0.396 mm for the fractal dimension using the tile counting method. The sizes were closely related to the morphometric parameters. Conclusion : The fractal dimension of mandibular trabecular bone, as calculated with the tile counting method, can be best characterized with a range of tile sizes from 0.132 to 0.396 mm.

• 대한교통학회지
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• 제22권6호
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• pp.109-120
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• 2004

1990년대 후반부터 구간 검지기를 이용한 링크통행시간 추정에 필요한 최소 표본수와 링크 및 경로 통행시간 추정과 예측을 위한 적정 집계간격에 대한 연구가 폭넓게 진행되어 왔다. 그러나 루프(지점)검지기를 이용한 교통정보수집체계의 경우, 합리적인 검증 없이 선정된 1분~5분의 집계간격을 이용하고 있다. 본 연구의 목적은 지점검지기인 루프검지기를 이용하여 통행시간자료를 수지하는 경우, 링크 및 경로 통행시간 추정과 예측을 위한 적정 집계간격 결정 모형을 개발하고 현장의 자료에 적용하는 것이다. 본 논문은 링크 및 경로 통행시간 추정을 위한 적정 집계간격 결정 모형으로 CVMSE(Cross Validated Mean Square Error)방법을 이용하였으며, 링크 및 경로 통행시간 예측을 위한 적정 집계간격 결정 모형으로는 FMSE(Forecasting Mean Square Error)를 적용하였다. 개발된 방법론은 경부고속도로의 루프이터에 적용되었다. 적용결과 링크 및 경로 통행시간 추정을 위한 적정 집계간격은 3분~5분으로, 링크 및 경로 통행시간 예측을 위한 적정 집계간격은 10~20분으로 분석되었다.

• 한국경제지리학회지
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• 제13권3호
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• pp.487-497
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• 2010

본 연구의 목적은 도시의 소득 및 지출함수를 이용하여 우리나라 7대 광역시의 인구규모가 적정 수준에 있는 지를 분석하는 것이다. 효용극대화 가계와 이윤극대화 생산자 문제의 균형인구를 완전경쟁조건으로부터 도출한 결과, 최적인구 규모는 도시의 기술수준 및 공공서비스 수준에 의해 결정된다. 이러한 측면에서 각 도시의 인구규모 수준을 살펴보면 서울, 부산, 대구, 인천 등은 과밀한 것으로 광주, 대전, 울산 등은 과소한 것으로 나타났다.

• 한국정밀공학회지
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• 제32권9호
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• pp.815-824
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• 2015

In this study, we conducted the approximate multi-objective optimization of gap sizes of pressurized-water reactor (PWR) annular fuels. To determine the contacting tendency of the inner-outer gaps between the annular fuel pellets and cladding, thermoelastic-plastic-creep (TEPC)analysis of PWR annular fuels was performed, using in-house FE code. For the efficient heat transfer at certain levels of stress, we investigated the tensile, compressive hoop stress and temperature, and optimized the gap sizes using the non-dominant sorting genetic algorithm (NSGA-II). For this, response surface models of objective and constraint functions were generated, using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by NSGA-II were verified through the TEPC analysis, and we compared the obtained optimum solutions and generated errors from the CCD and D-optimal design. We observed that optimum solutions differ, according to design of experiments (DOE) method.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.858-876
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• 2021

Although widely used, the design of the bulbous bow for ships has been difficult due to the complex interference between the wave system generated by the bulb and the wave system of the ship hull. Until now, a bulbous bow has been often designed using Kracht charts, which were established based on model test data, but these charts apply only to ships with a block coefficient C_B = 0.56-0.82, Froude number Fn = 0.20-0.40, and the obtained bulb sizes are only close to optimal. This paper presents a new method for the optimal design of bulbous bow, starting from the design of an initial bulb using Kracht charts for ships with any block coefficient or Froude number, then resizing this initial bulb to define the optimal bulb sizes based on a multi-objective function of the required power reduction, and a combined solution of Computation Fluid Dynamics (CFD) analysis and surrogate models. This study was applied to a fishing vessel FAO 75, which has been model tested and used to design steel fishing vessels in Vietnam recently. The obtained quantitative results showed the same trend as the theory and practice, with a reduction of the ship's required power by about 14%.

• 산업경영시스템학회지
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• 제40권1호
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• pp.95-104
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• 2017

This paper deals with solution methods for discrete and multi-valued optimization problems. The objective function of the problem incorporates noise effects generated in case that fitness evaluation is accomplished by computer based experiments such as Monte Carlo simulation or discrete event simulation. Meta heuristics including Genetic Algorithm (GA) and Discrete Particle Swarm Optimization (DPSO) can be used to solve these simulation based multi-valued optimization problems. In applying these population based meta heuristics to simulation based optimization problem, samples size to estimate the expected fitness value of a solution and population (particle) size in a generation (step) should be carefully determined to obtain reliable solutions. Under realistic environment with restriction on available computation time, there exists trade-off between these values. In this paper, the effects of sample and population sizes are analyzed under well-known multi-modal and multi-dimensional test functions with randomly generated noise effects. From the experimental results, it is shown that the performance of DPSO is superior to that of GA. While appropriate determination of population sizes is more important than sample size in GA, appropriate determination of sample size is more important than particle size in DPSO. Especially in DPSO, the solution quality under increasing sample sizes with steps is inferior to constant or decreasing sample sizes with steps. Furthermore, the performance of DPSO is improved when OCBA (Optimal Computing Budget Allocation) is incorporated in selecting the best particle in each step. In applying OCBA in DPSO, smaller value of incremental sample size is preferred to obtain better solutions.

• 설비공학논문집
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• 제9권4호
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• pp.552-560
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• 1997

Analysis is performed to determine the optimal lengths or cross-sectional areas of refrigerator-cooled current leads that can be applied to the conduction-cooled superconducting systems. The binary current lead is composed of the series combination of a normal metal at the upper(warm) part and a high $T_c$ superconductor(HTS) at the lower(cold) part. The heat conduction toward the cold end of HTS part constitutes a major refrigeration load. In addition, the joint between the parts should be cooled by a refrigerator in order to reduce the load at the low end and maintain the HTS part in a superconducting state. The sum of the work inputs required for the two refrigeration loads needs to be minimized for an optimal operation. In this design, three simple models that depict the refrigeration performance as functions of cooling temperature are developed based on some of the existing refrigerators. By solving one-dimensional conduction equation that take into account the temperature-dependent properties of the materials, the refrigeration works are numerically calculated for various values of the joint temperature and the sizes of two parts. The results show that for given size of HTS, there exist the optimal values for the joint temperature and the size of the normal metal. It is also found that the refrigeration work decreases as the length of HTS increases and that the optimal size of normal metal is quite independent of the size of HTS. For a given length of HTS, there is an optimal cross-sectional area and it increases as the length increases. The dependence of the optimal sizes on the refrigerator models employed are presented for 1kA leads.

• 전자공학회논문지B
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• 제32B권5호
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• pp.77-86
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• 1995

In this paper in order to reduce the encoding complexity required in the full search vector quantization(VQ), a new classified vector quantization(CVQ) technique is described employing the minimum-distance classifier. The determination of the optimal subcodebook sizes for each class is an important task in CVQ designs and is not an easy work. Therefore letting the subcodebook sizes be equal. A CVQ technique. Which satisties the optimal CVQ condition approximately, is proposed. The proposed CVQ is a kind of the partial search VQ because it requires a search process within each subcodebook only, and the minimum encoding complexity since the subcodebook sizes are the same in each class. But simulation results reveal while the encoding complexity is only O(N$^{1/2}$) comparing with O(N) of the full-search VQ. A simple systolic array, which has the through-put of k, is also proposed for the implementation of the VQ. Since the operation of the classifier is identical with that of the VQ, the proposed array is applied to both the classifier and the VQ in the proposed CVQ, which shows the usefulness of the proposed CVQ.