• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2005년도 춘계 학술대회논문집
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• pp.187-190
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• 2005

In this study, the reliablility based design optimization is peformed for an aircraft wing. The flexiblility of the wing was assumed by considering the interaction modeled by static aeroelasticity between aerodynamic forces and the structure. For a multidisciplinary design optimization the results of aerodynamic analysis and structural analysis were included in the optimization formulation. The First Order Reliability Method(FORM) was employed to consider the uncertainty of the designed points.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2005년도 제24회 춘계학술대회논문집
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• pp.11-15
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• 2005

공중발사 방식은 일반적인 지상발사와 비교해 볼 때 많은 장점을 지니고 있다. 그러나 공중발사 로켓의 형상은 모선에 장착 시 많은 제한이 따르기 때문에 여러 해석분야를 통합한 시스템 설계가 필요하다. 시스템 설계는 순차적 최적화와 MDF 기법을 이용하여 수행되었다. 해석 모듈은 임무분석, 단배분, 추진해석, 형상, 중량해석, 공력해석, 궤적해석을 포함한다. 두 가지 기법 중 MDF 기법을 이용하였을 때 더 좋은 결과를 도출하였다. 시스템 최적화 결과 총 중량 1244.91 kg. 위성중량 7.5 kg, 총 길이 6.18m, 지름 0.60 m을 지닌 초음속 공중발사 로켓이 설계되었다.

• 한국항공우주학회지
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• 제33권12호
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• pp.26-32
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• 2005

공중발사 방식은 일반적인 지상발사와 비교해 볼 때 많은 장점을 지니고 있다. 그러나 공중발사 로켓의 형상은 모선에 장착 시 많은 제한이 따르기 때문에 여러 해석분야를 통합한 시스템 설계가 필요하다. 시스템 설계는 순차적 최적화와 MDF 기법을 이용하여 수행되었다. 해석 모듈은 임무분석, 단배분, 추진해석, 형상, 중량해석, 공력해석, 궤적해석을 포함한다. 두 가지 기법 중 MDF 기법을 이용하였을 때 더 좋은 결과를 도출하였다. 시스템 최적화 결과 총 중량 1244.91kg, 위성중량 7.5kg, 총 길이 6.36 m, 지름 0.60m을 지닌 초음속 공중발사 로켓이 설계되었다.

• Structural Engineering and Mechanics
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• 제6권1호
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• pp.31-40
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• 1998

The research and applications of numerical methods of design optimization on structural dynamic behaviors are presented in this paper. The emphasis is focused on the dynamic design optimization of aerospace structures, particularly those composed of composite laminate and sandwich plates. The methods of design modeling, sensitivity analysis on structural dynamic responses, and the optimization solution approaches are presented. The numerical examples of sensitivity analysis and dynamic structural design optimization are given to demonstrate the effectiveness of the numerical methods.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2004년도 춘계 종합학술대회 논문집
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• pp.330-334
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• 2004

자바 바이트코드는 스택기반 코드이다. 스택기반 코드는 스택 접근 명령어를 사용하기 때문에 분석과 최적화를 어렵게 한다. 따라서 스택기반 코드 최적화에서 생기는 문제점인 코드의 단편화, 타입정보의 상실, 불필요한 적재와 저장이 나타날 수 있다. 바이트코드의 최적화와 분석의 어려운 문제점의 해결 방안으로 바이트코드 프레임워크를 설계한다. 본 논문은 바이트코드의 최적화와 분석의 문제점을 지적하고, 기존의 바이트코드 최적화 기술에 대한 연구 내용을 서술한다. 바이트코드의 분석과 최적화를 단순화하기 위한 대안으로 바이트코드 프레임워크를 제안한다.

• 정보저장시스템학회논문집
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• 제3권4호
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• pp.178-182
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• 2007

Topology optimization methods are classified into two methods such as the density method and the homogenization method. Those methods need to consider relationships between the material property and the density of each element in a design domain, the relaxation of the design space, etc. However, it is hard to apply on some cases due to the complexity to compose the design objective and its sensitivity analysis. In this paper, a modified topology optimization is proposed to assist designers who do not have mathematical or theoretical background of the topology optimization. In this study, optimal topology of structures can be achieved by the sequential design of experiment (DOE) and the sensitivity analysis. We conducted the DOE with an orthogonal array and the sensitivity analysis of design variables to determine sensitive variables used for connectivity between elements. The modified topology optimization method has advantages such as freedom from penalizing intermediate values and easy application with basic DOE concept.

• International Journal of Aeronautical and Space Sciences
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• 제17권2호
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• pp.268-283
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• 2016

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

• 한국자동차공학회논문집
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• 제6권1호
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• pp.1-15
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• 1998

Currently, computational analysis is a popular technology in automobile engineering. Finite element analysis is an excellent method for body analysis. For finite element analysis, accurate modeling is very important to obtain precise information. Stick modeling is a convenient way in that it is easy and simple. When a stick model is utilized, the joints are modified in the tuning process. A tuning method for the joint has been developed. The joints are modeled by designated beam elements. An optimization method called "Goal Programming" is employed to impose the target values. With the tuned joints, the entire optimization has been carried out. Using the "Recursive Quadratic Programming" algorithm, the optimization process determines the configuration of the entire structure and sizes of all the sections. For example, the structure of an electrical vehicle is modeled and analyzed by the method. The stick model works well since the structure is made of aluminium frames. Although the example handles an electrical vehicle, this method can be applied to general vehicle structures.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• Structural Engineering and Mechanics
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• 제36권1호
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• pp.79-94
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• 2010

This study shows how uncertainties of data like material properties quantitatively have an influence on structural topology optimization results for dynamic problems, here such as both optimal topology and shape. In general, the data uncertainties may result in uncertainties of structural behaviors like deflection or stress in structural analyses. Therefore optimization solutions naturally depend on the uncertainties in structural behaviors, since structural behaviors estimated by the structural analysis method like FEM need to execute optimization procedures. In order to quantitatively estimate the effect of data uncertainties on topology optimization solutions of dynamic problems, a so-called interval analysis is utilized in this study, and it is a well-known non-stochastic approach for uncertainty estimate. Topology optimization is realized by using a typical SIMP method, and for dynamic problems the optimization seeks to maximize the first-order eigenfrequency subject to a given material limit like a volume. Numerical applications topologically optimizing dynamic wall structures with varied supports are studied to verify the non-stochastic interval analysis is also suitable to estimate topology optimization results with dynamic problems.