• Structural Engineering and Mechanics
• /
• 제67권3호
• /
• pp.245-254
• /
• 2018

In this paper, a Cloud Model based Fruit Fly Optimization Algorithm (CMFOA) is presented for structural damage identification, which is a global optimization algorithm inspired by the foraging behavior of fruit fly swarm. It is assumed that damage only leads to the decrease in elementary stiffness. The differences on time-domain structural acceleration data are used to construct the objective function, which transforms the damaged identification problem of a structure into an optimization problem. The effectiveness, efficiency and accuracy of the CMFOA are demonstrated by two different numerical simulation structures, including a simply supported beam and a cantilevered plate. Numerical results show that the CMFOA has a better capacity for structural damage identification than the basic Fruit Fly Optimization Algorithm (FOA) and the CMFOA is not sensitive to measurement noise.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 1999년도 가을 학술발표회 논문집
• /
• pp.359-369
• /
• 1999

The paper describes the study of concurrent subspace optimization(CSSO) for coupled multidisciplinary design optimization (MDO) techniques in mechanical systems. This method is a solution to large scale coupled multidisciplinary system, wherein the original problem is decomposed into a set of smaller, more tractable subproblems. Key elements in CSSO are consisted of global sensitivity equation(GSE), subspace optimization (SSO), optimum sensitivity analysis(OSA), and coordination optimization problem(COP) so as to inquiry valanced design solutions finally, Automatic differentiation has an ability to provide a robust sensitivity solution, and have shown the numerical numerical effectiveness over finite difference schemes wherein the perturbed step size in design variable is required. The present paper will develop the automatic differentiation based concurrent subspace optimization(AD-CSSO) in MDO. An automatic differentiation tool in FORTRAN(ADIFOR) will be employed to evaluate sensitivities. The use of exact function derivatives in GSE, OSA and COP makes Possible to enhance the numerical accuracy during the iterative design process. The paper discusses how much influence on final optimal design compared with traditional all-in-one approach, finite difference based CSSO and AD-CSSO applying coupled design variables.

• Nuclear Engineering and Technology
• /
• 제53권11호
• /
• pp.3772-3783
• /
• 2021

This work proposes a new efficient meta-heuristic optimization algorithm called Gamma Ray Interactions Based Optimization (GRIBO). The algorithm mimics different energy loss processes of a gamma-ray photon during its passage through a matter. The proposed novel algorithm has been applied to search for the global minima of 30 standard benchmark functions. The paper also considers solving real optimization problem in the field of nuclear engineering, radioisotope identification. The results are compared with those obtained by the Particle Swarm Optimization, Genetic Algorithm, Gravitational Search Algorithm and Grey Wolf Optimizer algorithms. The comparisons indicate that the GRIBO algorithm is able to provide very competitive results compared to other well-known meta-heuristics.

• 한국강구조학회 논문집
• /
• 제14권6호
• /
• pp.783-791
• /
• 2002

본 논문에서는 지진하중을 받는 강뼈대구조물의 표준단면에 대한 다목적 최적설계 정식화 방법을 제안하였다. 다목적 최적화 문제는 강재중량, 변형에너지, 안전성을 목적함수로 구성하였다. 표준단면제원을 이용한 다목적 최적설계 문제를 효율적으로 해결하기 위하여 전역기준법(Global Criterion Method)을 이용하였다. 실제적인 대형구조물의 다목적 최적설계 문제를 효율적으로 해결하기 위해 전체 구조계와 구조 요소계로 나누는 다단계 알고리즘을 적용하였고 자동미분을 이용하여 매개변수에 대한 민감도해석을 이용한 근사재해석 기법을 사용하였다. 또한 전체 구조계와 구조 요소계의 연결을 위해 표준단면을 이용하여 단면 2차 모멘트와 단면적, 단면상수와의 관계를 희귀분석 하였다. 수치해석 결과 안정성을 고려한 강 뼈대 구조물의 최적설계 방법은 기존의 방법보다 합리적인 설계를 유도할 것으로 기대된다.

• 한국산학기술학회논문지
• /
• 제17권3호
• /
• pp.117-126
• /
• 2016

본 연구에서는 안경의 광학적 특성에서 고안된 새로운 메타휴리스틱 최적화 알고리즘인 Vision Correction Algorithm(VCA)을 개발하였다. VCA는 안경광학분야에서 수행되는 검안과 교정과정을 최적해 탐색 과정에 적용한 기법으로 근시/원시교정-밝기조정-압축시행-난시교정의 과정을 거쳐 최적화를 수행하게 된다. 제안된 VCA는 기존의 메타휴리스틱 알고리즘과 달리 현재까지 축적된 최적화 결과를 기반으로 전역탐색과 국지탐색 적용 확률, 그리고 전역탐색의 방향이 자동적으로 조정 된다. 제안된 방법을 대표적인 최적화 문제(수학 및 공학 분야)에 적용하고, 그 결과를 기존 알고리즘들과 비교하여 제시하였다.

• 한국항공우주학회지
• /
• 제37권8호
• /
• pp.737-743
• /
• 2009

본 연구는 Tabu Search를 이용하여 LHP의 최적설계를 진행하는 방법과 절차 및 결과를 제시하고자 한다. 최적설계의 목적은 항공기에 탑재된 리튬이온 전지의 작동온도 조건을 만족하면서 LHP의 중량을 최소화시키는 것이다. 전지는 고에너지 밀도의 특성으로 항공기에 장착된 고에너지 레이저의 동력원으로 사용되는 것으로 가정되었다. 해석은 Steady state analysis model에 기초하였으며 메타모델로 근사화하였다. 최적화 결과로 Tabu Search는 유전알고리듬 등 다른 비 구배기반 최적화 방법에 비해 비교적 적은 계산 시간을 소요하면서도 전역해를 보장하였으나 난수에 의해 초기해를 바꾸어 가면서 최적화를 여러 번 시도해야 하는 단점이 있었다. 그리고 최적화 과정을 통해 기 발표된 LHP와 동일한 성능을 가지면서도 경량화된 LHP를 얻을 수 있었다.

• Steel and Composite Structures
• /
• 제25권6호
• /
• pp.663-670
• /
• 2017

The problem of layup optimization of the composite laminates involves a very complex multidimensional solution space which is usually non-exhaustively explored using different heuristic computational methods such as genetic algorithms (GA). To ensure the convergence to the global optimum of the applied heuristic during the optimization process it is necessary to evaluate a lot of layup configurations. As a consequence the analysis of an individual layup configuration should be fast enough to maintain the convergence time range to an acceptable level. On the other hand the mechanical behavior analysis of composite laminates for any geometry and boundary condition is very convoluted and is performed by computational expensive numerical tools such as finite element analysis (FEA). In this respect some studies propose very fast FEA models used in layup optimization. However, the lower bound of the execution time of FEA models is determined by the global linear system solving which in some complex applications can be unacceptable. Moreover, in some situation it may be highly preferred to decrease the optimization time with the cost of a small reduction in the analysis accuracy. In this paper we explore some machine learning techniques in order to estimate the failure of a layup configuration. The estimated response can be qualitative (the configuration fails or not) or quantitative (the value of the failure factor). The procedure consists of generating a population of random observations (configurations) spread across solution space and evaluating using a FEA model. The machine learning method is then trained using this population and the trained model is then used to estimate failure in the optimization process. The results obtained are very promising as illustrated with an example where the misclassification rate of the qualitative response is smaller than 2%.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 1998년도 춘계학술대회논문집; 용평리조트 타워콘도, 21-22 May 1998
• /
• pp.81-87
• /
• 1998

In this paper, a global acoustic design sensitivity analysis (DSA) of field point pressure with respect to structural sizing design variables is developed. Firstly acoustic sensitivity is formulated and implemented numerically. And it is combined with continuum structural sensitivity to obtain the global acoustic, design sensitivity. For this procedure, GASA (global acoustic design sensitivity analyzer) has been developed. A half scale of automobile cavity model is considered in this paper. In order to confirm accuracy of the results of global acoustic DSA obtained by GASA, it is compared with the result of central finite difference method. In order to reduce computation time, Rayleigh approximated solution is evaluated and compared with the solution which used every nodal velocities. Also the acoustic optimization procedure is performed using design sensitivities. From these numerical studies, it can be shown that global acoustic DSA is a useful tool to improve acoustic problems.

• 대한기계학회논문집A
• /
• 제27권8호
• /
• pp.1353-1362
• /
• 2003

This paper considers a simultaneous optimization problem of structure and control systems. The problem is generally formulated as a non-convex optimization problem for the design parameters of mechanical structure and controller. Therefore, it is not easy to obtain the global solutions for practical problems. In this paper, we parameterize all design parameters of the mechanical structure such that the parameters work in the control system as decentralized static output feedback gains. Using this parameterization, we have formulated a simultaneous optimization problem in which the design specification is defined by the Η$_2$and Η$\_$$\infty$/ norms of the closed loop transfer function. So as to lead to a convex problem we approximate the nonlinear terms of design parameters to the linear terms. Then, we propose a convex optimization method that is based on linear matrix inequality (LMI). Using this method, we can surely obtain suboptimal solution for the design specification. A numerical example is given to illustrate the effectiveness of the proposed method.

• Journal of Mechanical Science and Technology
• /
• 제16권8호
• /
• pp.1033-1038
• /
• 2002

Genetic alsorithm (GA) , compared to the gradient-based optimization, has advantages of convergence to a global optimized solution. The genetic algorithm requires so many number of analyses that may cause high computational cost for genetic search. This paper proposes a personal computer network programming based on TCP/IP protocol and client-server model using socket, to improve processing speed of the genetic algorithm for optimization of composite laminated structures. By distributed processing for the generated population, improvement in processing speed has been obtained. Consequently, usage of network-based genetic algorithm with the faster network communication speed will be a very valuable tool for the discrete optimization of large scale and complex structures requiring high computational cost.