• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
• /
• pp.993-996
• /
• 2006

NOAA operational bulk SST product (Reynolds et al, 2002) is very popular global SST data sets and is extensively used for various studies. However, the original time resolution is weekly and relatively large. On the other hand, there exist many new global SST data sets at present. In this study, we compare many global SST data sets including NOAA operational bulk SST product, CAOS OI SST product, Microwave Optimum Interpolation (MWOI) SST, Real Time Global (RTG) SST and JMA merged satellite and in situ Global Daily (MGD) SST.

• 한국공간구조학회논문집
• /
• 제12권2호
• /
• pp.89-98
• /
• 2012

본 연구는 공간 트러스의 전체 좌굴을 고려한 최적 구조설계에 대해 연구를 하였으며, 구조물의 최소중량을 구하는 것이 목적이다. 응력제약에 의한 부재 최적화를 위해서 수리 계획법이 사용되었으며, 뜀-좌굴을 고려하기 위해 동적 계획법을 적용하였다. 트러스 부재의 최적설계를 위한 수리 모형은 전체중량 목적함수와 인장 또는 압축 허용응력 및 세장비 제약식으로 구성하였다. 평형경로상의 임계점 즉 좌굴하중을 구하기 위해서 접선 강성행렬의 행렬식 변화를 조사하였으며, 설계하중에 대한 좌굴하중 비율이 동적계획법의 반복계산과정에서 공간 트러스의 강성을 조절하기위해 반영되었다. 제안된 최적설계 프로세서의 검증을 위해서 스타 돔 구조물 예제를 통해 조사하였으며, 수치 결과는 잘 수렴하고 모든 제약을 만족하였다. 제시된 최적설계 프로세스는 전체좌굴을 고려한 최적설계를 수행하기 위한 비교적 간단 방법이고, 실무 구조설계를 반영하는데 가능하다.

• 콘크리트학회논문집
• /
• 제12권4호
• /
• pp.91-101
• /
• 2000

As the computer related technology evolves a study for a practical use of real structure as well as its hteory for optimum design has been greatly advanced. But the study on optimum design of pre-stressed concrete beam(PSC-beam) bridge for the construction of national roads and highways in Korea is not sufficient. Since a standard section for the PSC-beam is proposed, it is practically used in designing the PSC-beam. It is noticed that the section using the current standard PSC-beam design to be an over-designed with its surplus safety factor. Therefore, it is necessary to consider economical PSC-beam section which automatically satisfies all requirement of design specifications. Thus, in this study, the optimum design methods of PSC-beam are carried out using the gradient-based search method and global search method. As a result of the optimum design method, it was confirmed that the design of PSC-beam has a serious properties to non-linearity and discontinuity. And the section that in economical and efficinet design methods than the current standard design method is proposed.

• 동력기계공학회지
• /
• 제7권3호
• /
• pp.29-34
• /
• 2003

Genetic algorithm is a optimization technique based on the mechanics of natural selection and natural genetics. Global optimum solution can be obtained efficiently by operations of reproduction, crossover and mutation in genetic algorithm. The authors developed a computer program which can optimize marine propulsion shafting by using binary-coded genetic algorithm and modal analysis method. In order to confirm the effectiveness of the developed computer program, we apply the program to a optimum design problem which is to obtain optimum diameters of intermediate shaft and propeller shaft in marine propulsion shafting. Objective function is to minimize total mass of shafts and constraints are that torsional vibration stresses of shafts in marine propulsion shafting can not exceed the permissible torsional vibration stresses of the ship classification society. The computational results by the program were compared with those of conventional design technique.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2003년도 추계학술대회논문집
• /
• pp.121-126
• /
• 2003

This paper describes the optimum design for journal bearing by using simulated annealing method. Simulated annealing algorithm is an optimum design method to calculate global and local optimum solution. Dynamic characteristics of a journal bearing are calculated by using finite difference method (FDM), and these values are used for the procedure of journal bearing optimization. The objective is to minimize the resonance response (Q factor) of the simple rotor system. Bearing clearance and length to diameter ratio are used as the design variables.

• 한국해양공학회지
• /
• 제27권5호
• /
• pp.36-42
• /
• 2013

We present the optimum design for the cross-sectional(sizing) and shape optimization of truss structures with natural frequency constraints. The optimum design method used in this paper employs continuous design variables and the Harmony Search Algorithm(HSA). HSA is a meta-heuristic search method for global optimization problems. In this paper, HSA uses the method of random number selection in an update process, along with penalty parameters, to construct the initial harmony memory in order to improve the fitness in the initial and update processes. In examples, 10-bar and 72-bar trusses are optimized for sizing, and 37-bar bridge type truss and 52-bar(like dome) for sizing and shape. Four typical truss optimization examples are employed to demonstrate the availability of HSA for finding the minimum weight optimum truss with multiple natural frequency constraints.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 2000년도 봄 학술발표회논문집
• /
• pp.449-457
• /
• 2000

The paper describes the study of global approximate optimization utilizing soft computing techniques such as genetic algorithms (GA's), neural networks (NN's), and fuzzy inference systems(FIS). GA's provide the increasing probability of locating a global optimum over the entire design space associated with multimodality and nonlinearity. NN's can be used as a tool for function approximations, a rapid reanalysis model for subsequent use in design optimization. FIS facilitates to handle the quantitative design information under the case where the training data samples are not sufficiently provided or uncertain information is included in design modeling. Properties of soft computing techniques affect the quality of global approximate model. Evolutionary fuzzy modeling (EFM) and adaptive neuro-fuzzy inference system (ANFIS) are briefly introduced for structural optimization problem in this context. The paper presents the success of EFM depends on how optimally the fuzzy membership parameters are selected and how fuzzy rules are generated.

• 대한기계학회논문집A
• /
• 제25권4호
• /
• pp.671-684
• /
• 2001

Several design problems of composite structures are studied via a global optimizer based on attraction regions. MSC/NASTRAN is adopted for static and eigenvalue analysis. The method of modified feasible direction in DOT is used for local optimization. Through the review of global optimization algorithms, the triangular patch algorithm is selected because the algorithm is known to be efficient, robust and powerful for general nonlinear optimization problems. For general applicability, various mechanical properties are considered as design objectives; strain energy, eigenvalue, weight, displacement, and buckling load. In all cases considered, the triangular patch algorithm results in a lot of optimum points and useful design patterns, that are not easy by local algorithms or conventional global algorithms can be determined.

• Steel and Composite Structures
• /
• 제19권4호
• /
• pp.995-1009
• /
• 2015

This study presents design optimization of spot welded structures to attain maximum strength by using the Nelder-Mead (Simplex) method. It is the main idea of the algorithm that the simulation run is executed several times to satisfy predefined convergence criteria and every run uses the starting points of the previous configurations. The material and size of the sheet plates are the pre-assigned parameters which do not change in the optimization cycle. Locations of the spot welds, on the other hand, are chosen to be design variables. In order to calculate the objective function, which is the maximum equivalent stress, ANSYS, general purpose finite element analysis software, is used. To obtain global optimum locations of spot welds a methodology is proposed by modifying the Nelder-Mead (Simplex) method. The procedure is applied to a number of representative problems to demonstrate the validity and effectiveness of the proposed method. It is shown that it is possible to obtain the global optimum values without stacking local minimum ones by using proposed methodology.

• Structural Monitoring and Maintenance
• /
• 제1권4호
• /
• pp.427-449
• /
• 2014

A hybrid optimization method for the identification of state-space models is presented in this study. Hybridization is succeeded by combining the advantages of deterministic and stochastic algorithms in a superior scheme that promises faster convergence rate and reliability in the search for the global optimum. The proposed hybrid algorithm is developed by replacing the original stochastic mutation operator of Evolution Strategies (ES) by the Levenberg-Marquardt (LM) quasi-Newton algorithm. This substitution results in a scheme where the entire population cloud is involved in the search for the global optimum, while single individuals are involved in the local search, undertaken by the LM method. The novel hybrid identification framework is assessed through the Monte Carlo analysis of a simulated system and an experimental case study on a shear frame structure. Comparisons to subspace identification, as well as to conventional, self-adaptive ES provide significant indication of superior performance.