• Structural Engineering and Mechanics
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• 제81권3호
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• pp.367-378
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• 2022

In this study, combined size and shape optimization of spatial truss tower structures are presented by using new optimization algorithms named Rao-1, and Rao-2. The nodal displacements, allowable stress and buckling for compressive members are taken into account as structural constraints for truss towers. The discrete and continuous design variables are used as design variables for size and shape optimization. To show the efficiency of the proposed optimization algorithm, 25-bar, and 39-bar 3D truss towers are solved for combined size and shape optimization. The 72-bar, and 160-bar 3D truss towers are solved only by size optimization. The optimal results obtained from this study are compared to those given in the literature to illustrate the efficiency and robustness of the proposed algorithm. The structural analysis and the optimization process are coded in MATLAB programming.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.616-619
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• 2000

The optimum design of a structure requires to determine economical member size and shape of a structure which satisfies the design conditions and functions. In this study, it is attempted to minimize a dead weight of the bogie frame. Therefore, shape optimization is performed for a bolster rib at first and then size optimization for the thickness of top and bottom plate. For the efficient reduction of a weight of a bogie frame, various ellipses centered at a centroid of a bolster rib are made and tried. For the shape optimization, a major axis and an eccentricity of an ellipse are chosen as design variables. From the numerical results of shape and size optimization of a bogie frame, it is known that the weight can be reduced up to 12.476 Y4717.21 kg) with displacement and stress constraints.

• Structural Engineering and Mechanics
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• 제76권6호
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• pp.799-821
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• 2020

The optimum design of truss structures is one of the significant categories in structural optimization that has widely been applied by researchers. In the present study, new mathematical programming called Consistent Approximation (CONAP) method is utilized for the simultaneous optimization of the size and shape of truss structures. The CONAP algorithm has already been introduced to optimize some structures and functions. In the CONAP algorithm, some important parameters are designed by employing design sensitivities to enhance the capability of the method and its consistency in various optimum design problems, especially structural optimization. The cross-sectional area of the bar elements and the nodal coordinates of the truss are assumed to be the size and shape design variables, respectively. The displacement, allowable stress and the Euler buckling stress are taken as the design constraints for the problem. In the proposed method, the primary optimization problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the sequential quadratic programming (SQP) algorithm. Several truss structures are designed by employing the CONAP method to illustrate the efficiency of the algorithm for simultaneous shape and size optimization. The optimal solutions are compared with some of the mathematical programming algorithms, the approximation methods and metaheuristic algorithms those reported in the literature. Results demonstrate that the accuracy of the optimization is improved and the convergence rate speeds up.

• 한국강구조학회 논문집
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• 제12권5호통권48호
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• pp.515-525
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• 2000

본 연구의 목적은 평면 트러스의 단면치수 및 형 상 최적화 알고리즘을 개발 하는 것이다. 본 연구에 적용된 최적화 기법은 무제약 축차선형화기법(SUMT)의 extended penalty method와 다변수(多變數)를 가지는 직접탐사법인 Hooke & Jeeves method이다. 상기(上記) 언급된 두 방법은 단면최적화와 형상최적화 과정의 각 단계에서 반복적 다 최적설계 과정에서 최종의 최적값이 구해질 때까지 단면최적화와 형상최적화 과정이 반복적으로 상호작용하게 된다. 트러스의 형상최적화에 관한 기존의 연구문헌에서는 최적화의 설계변수로서 부재의 단면적과 절점좌표를 사용하였다. 이렇게 할 경우, 압축재의 좌굴특성을 제대로 반영하기 어려우므로 한정된 조건으로 좌굴특성을 부여하게 되어 보다 실제적인 최적설계에 많은 제약을 가져오게 되므로 본 연구에서는 부재의 실제치수와 절점좌표를 최적화의 설계 변수로 취하게 되므로 부재치수의 변화에 따른 좌굴특성의 변화를 최대한 반영할 수 있다.

• 한국공간구조학회논문집
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• 제10권4호
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• pp.59-66
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• 2010

본 연구는 스페이스 트러스 구조물의 초기 형상을 결정하기 위해 밀도법을 이용한 위상최적화 기술을 고려하고자 한다. 대부분의 초기 형상설계는 다양한 최적화 방법을 활용하지 않고 설계자의 경험이나 시행착오적인 방법을 바탕으로 수행되고 있다. 이런 이유로 합리적이고 경제적인 최적화기술이 초기 형상설계에 도입되어야 한다. 따라서 본 연구에서는 스페이스 트러스 구조물을 대상으로 설계영역을 설정하고 위상최적화를 수행하여 최적의 재료분포를 찾은 뒤 크기최적화를 이용하여 최적부재 크기를 찾고자 한다. 이와 같이 밀도법을 이용한 위상 및 크기최적화를 병행하여 수행할 경우 합리적인 스페이스 트러스 구조물의 초기 형상을 도출할 수 있다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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• pp.151-160
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• 2004

Genetic algorithm is the theory of grafting the principle of survival of the fittest in genetics on to the computer algorithm and it is used to solve the optimization problems, especially the shape and size optimization of the structure in Architectural problems. In the size optimization problem discrete variables are used, but series variables have to be used in the shape optimization problem because of the incongruenty. The purpose of this study is to obtain the optimum shape of cable domes by using the real coding genetic algorithm. Generally, the structural performance of the cable domes is influenced very sensitively by pre-stress, geometry and length of the mast because of its flexible characteristic. So, it is very important to decide the optimum shape to get maximum stiffness of cable domes. We use the model to verify the usefulness of this algorithm for shape optimization and analyze the roof system of Seoul Olympic Gymnastic Arena as analytical model of a practical structures. It is confirmed lastly that the optimum shape domes have more stiffness than initial shape ones.

• Structural Engineering and Mechanics
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• 제53권4호
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• pp.833-845
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• 2015

Natural frequencies of the structural systems should be far away from the excitation frequency in order to avoid or reduce the destructive effects of dynamic loads on structures. To accomplish this goal, a structural optimization on size and shape has been performed considering frequency constraints. Such an optimization problem has highly nonlinear property. Thus, the quality of the solution is not independent of the optimization technique to be applied. This study presents the performance evaluation of the recently proposed meta-heuristic algorithm called Teaching Learning Based Optimization (TLBO) as an optimization engine in the weight optimization of the truss structures under frequency constraints. Some examples regarding the optimization of trusses on shape and size with frequency constraints are solved. Also, the results obtained are tabulated for comparison. The results demonstrated that the performance of the TLBO is satisfactory. Additionally, TLBO is better than other methods in some cases.

• Steel and Composite Structures
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• 제33권5호
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• pp.747-753
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• 2019

Metaheuristic algorithm is used to solve the weight minimization problem of truss structures considering shape, and sizing design variables. The cross-sectional areas of the line element in trusses are the design variables for size optimization and the changeable joint coordinates are the shape optimization used in this study. The design of plane and spatial truss structures are optimized by metaheuristic technique named Teaching-Learning-Based Optimization (TLBO). Finite element analyses of structures and optimization process are carried out by the computer program visually developed by the authors coded in MATLAB. The four benchmark problems (trusses 2D ten-bar, 3D thirty-seven-bar, 3D seventy-two-bar and 2D two-hundred-bar) taken from literature are optimized and the optimal solution compared the results given by previous studies.

• 한국공간정보시스템학회:학술대회논문집
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• 한국공간정보시스템학회 2004년도 춘계 학술발표회 논문집 제1권1호(통권1호)
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• pp.43-52
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• 2004

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algerian was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• Advances in aircraft and spacecraft science
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• 제4권4호
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• pp.467-486
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• 2017

A method for decoupling reliability based design optimization problem into a set of deterministic optimization and performing a reliability analysis is described. The inner reliability analysis and the outer optimization are performed separately in a sequential manner. Since the outer optimizer must perform a large number of iterations to find the optimized shape and size of structure, the computational cost is very high. Therefore, during the course of this research, new multilevel reliability optimization methods are developed that divide the design domain into two sub-spaces to be employed in an iterative procedure: one of the shape design variables, and the other of the size design variables. In each iteration, the probability constraints are converted into equivalent deterministic constraints using reliability analysis and then implemented in the deterministic optimization problem. The framework is first tested on a short column with cross-sectional properties as design variables, the applied loads and the yield stress as random variables. In addition, two cases of curvilinearly stiffened panels subjected to uniform shear and compression in-plane loads, and two cases of curvilinearly stiffened panels subjected to shear and compression loads that vary in linear and quadratic manner are presented.