• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2006년도 추계 학술대회논문집
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• pp.28-29
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• 2006

Computational approaches for the aerodynamic design and optimization are introduced. In this paper the aerodynamic design methods and applications, which have been applied to various aerospace vehicles at Konkuk University, are introduced. It is shown that system approximation technique reduces computational cost for CFD analysis and improves efficiency for the design optimization process.

• 정보교육학회논문지
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• 제16권3호
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• pp.319-326
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• 2012

본 논문에서는 Computational literacy교육에서 Computational Thinking을 향상시키기 위하여 디자인 기반 학습을 제안하였다. 디자인 기반 학습은 CT를 길러주기 위하여 CL교육에서 시도하는 학습 방법으로 MIT의 연구를 바탕으로 본 연구에 맞게 수정, 보완하여 적용하였다. 초등학교 4학년 단위 영재학급 학생을 대상으로 EPL교육을 실시한 후 교육전략 및 시사점을 도출하였다. 교육효과를 검증하기 위해 설문조사 및 관찰, 인터뷰를 실시하고 그 결과를 분석하였다. 연구 결과, CL학습에서의 디자인 기반 학습은 self-프로그래밍 능력과 흥미도를 긍정적으로 변화시켰고 학습자들이 자신의 아이디어를 창작물로 제작하고 의미있는 결과물을 만드는 교육에 효과적인 것으로 나타났다. 본 연구가 컴퓨터 교육에서 디자인 기반학습을 효과적으로 적용하는데 필요한 기초자료로 제공되길 기대한다.

• Steel and Composite Structures
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• 제27권3호
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• pp.297-310
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• 2018

A simple and efficient numerical optimization approach for the lightweight optimal design of composite laminated beams is presented in this paper. The proposed procedure is a combination between the finite element method (FEM) and a global optimization algorithm developed recently, namely Jaya. In the present procedure, the advantages of FEM and Jaya are exploited, where FEM is used to analyze the behavior of beam, and Jaya is modified and applied to solve formed optimization problems. In the optimization problems, the objective aims to minimize the overall weight of beam; and fiber volume fractions, thicknesses and fiber orientation angles of layers are selected as design variables. The constraints include the restriction on the first fundamental frequency and the boundaries of design variables. Several numerical examples with different design scenarios are executed. The influence of the design variable types and the boundary conditions of beam on the optimal results is investigated. Moreover, the performance of Jaya is compared with that of the well-known methods, viz. differential evolution (DE), genetic algorithm (GA), and particle swarm optimization (PSO). The obtained results reveal that the proposed approach is efficient and provides better solutions than those acquired by the compared methods.

• 인터넷정보학회논문지
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• 제19권1호
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• pp.123-130
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• 2018

With the emergence of a new paradigm called Open Science and Big Data, the need for data sharing and collaboration is also emerging in the computational science field. This paper, we analyzed data-driven research cases for computational science by field; material design, bioinformatics, high energy physics. We also studied the characteristics of the computational science data and the data management issues. To manage computational science data effectively it is required to have data quality management, increased data reliability, flexibility to support a variety of data types, and tools for analysis and linkage to the computing infrastructure. In addition, we analyzed trends of platform technology for efficient sharing and management of computational science data. The main contribution of this paper is to review the various computational science data repositories and related platform technologies to analyze the characteristics of computational science data and the problems of data management, and to present design considerations for building a future computational science data platform.

• 한국전산유체공학회지
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• 제8권4호
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• pp.50-57
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• 2003

Cross-flow fans are widely used in various applications, due to their large capacity of mass flow and size compactness. The flow field of the cross-flow fan is, however, complex and has many design parameters. Thus, the general design guide has not been sufficiently established yet and the design strategies of cross-flow fans have been mostly based on experiments. In the present study, the performance and their two-dimensional flow characteristics are numerically analyzed by using the STAR-CD(commercial computational fluid dynamics code). The simulation is done by varying the several design parameters such as the impeller blade shapes and the gap between the stabilizer and impeller. The computational results are compared with the experimental data at the fan outlet region. Finally, some helpful guides for the optimum design of cross-flow fans are proposed.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2004년도 추계 학술대회논문집
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• pp.187-191
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• 2004

The conventional reliability based design optimization(RBDO) methods require high computational cost compared with the deterministic design optimization(DO) methods. To overcome the computational inefficiency of RBDO, single loop methods have been proposed. These need less function calls than that of RBDO but much more than that of DO. In this study, the approximate reliability method is proposed that the computational requirement is nearly the same as DO and the reliability accuracy is good compared with that of RBDO. Using this method, the 3-D viscous aerodynamic shape design optimization with uncertainty is performed very efficiently.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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• pp.275-283
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• 2004

The paper describes the integrated design system using MDO and approximation technique. In MDO related research, final target is an integrated and automated MDO framework systems. However, in order to construct the integrated design system, the prerequisite condition is how much save computational cost because of iterative process in optimization design and lots of data information in CAD/CAE integration. Therefore, this paper presents that an efficient approximation method, Adaptive Approximation, is a competent strategy via MDO framework systems.

• 전산구조공학
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• 제22권5호
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• pp.8-14
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• 2009

• 한국CDE학회논문집
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• 제1권3호
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• pp.242-256
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• 1996

Although feature-based design is a promising approach to fully integrating CAD/CAM, current feature-based design approaches seldom provide methodologies to easily define and design features. This paper proposes a new approach to integrating parametric design with feature-based design to overcome those limitations by globally decomposing a design into a set of features and locally defining and positioning each feature by geometric constraints. Each feature is defined as a parametric shape which consists of a feature section, attributes, and a set of constraints. The generalized sketching and sweeping techniques are used to simplify the process of designing features. The proposed approach is knowledge-based and its computational efficiency in geometric reasoning is improved greatly. Parametrically designed features not only have the advantage of allowing users to efficiently perform design changes, but also provide designers with a natural design environment in which they can do their work more naturally and creatively.

• 한국CDE학회논문집
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• 제5권2호
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• pp.127-135
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• 2000

Emergent computing paradigms such as genetic algorithms have found increased use in problems in engineering design. These computational tools have been shown to be applicable in the solution of generically difficult design optimization problems characterized by nonconvexities in the design space and the presence of discrete and integer design variables. Another aspect of these computational paradigms that have been lumped under the bread subject category of soft computing, is the domain of artificial intelligence, knowledge-based expert system, and machine learning. The paper explores a machine learning paradigm referred to as teaming classifier systems to construct the high-quality global function approximations between the design variables and a response function for subsequent use in design optimization. A classifier system is a machine teaming system which learns syntactically simple string rules, called classifiers for guiding the system's performance in an arbitrary environment. The capability of a learning classifier system facilitates the adaptive selection of the optimal number of training data according to the noise and multimodality in the design space of interest. The present study used the polynomial based response surface as global function approximation tools and showed its effectiveness in the improvement on the approximation performance.