• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.369-372
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• 2000

ESO(Evolutionary Structural Optimization) method is known that elements involved low stress value are removed from the previous model or that elements are added around elements involved high stress level on it and then the optimized model is obtained with required weight. Rejection ratio/addition ratio and evolutionary ratio are predefined and elements having lower/higher stress than reference stress, which average Mises stress on edge elements times rejection ratio, are deleted/added. In this study, when the plate having a cutout is subjected various in-plane load, a cutout shape is optimized using ESO method. ANSYS is used to analyse a finite element model and optimization procedure is made by APDL (ANSYS Parametric Design Language). ESO method is useful in rather than a complex structure optimization as well as a cutout shape optimization.

• 대한기계학회논문집A
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• 제25권9호
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• pp.1444-1451
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• 2001

The evolutionary structural optimization(ESO) method has been under continuous development since 1992. The bidirectional evolutionary structural optimization(BESO) method is made of additive and removal procedure. The BESO method is very useful to search the global optimum and to reduce the computational time. This paper presents the ranked bidirectional evolutionary structural optimization(R-BESO) method which adds elements based on a rank, and the performance indicator which can estimate a fully stressed model. The R-BESO method can obtain the optimum design using less iteration number than iteration number of the BESO.

• Structural Engineering and Mechanics
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• 제27권1호
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• pp.49-61
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• 2007

This paper presents a modified and improved bi-directional evolutionary structural optimization (BESO) method for topology optimization. A sensitivity filter which has been used in other optimization methods is introduced into BESO so that the design solutions become mesh-independent. To improve the convergence of the optimization process, the sensitivity number considers its historical information. Numerical examples show the effectiveness of the modified BESO method in obtaining convergent and mesh-independent solutions. A study of the effects of various BESO parameters on the solution is then conducted to determine the appropriate values for these parameters.

• Journal of Mechanical Science and Technology
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• 제14권9호
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• pp.913-919
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• 2000

The purpose of this study was to develop a new element removal method for ESO (Evolutionary Structural Optimization), which is one of the topology optimization methods. ESO starts with the maximum allowable design space and the optimal topology emerges by a process of removal of lowly stressed elements. The element removal ratio of ESO is fixed throughout topology optimization at 1 or 2%. BESO (bidirectional ESO) starts with either the least number of elements connecting the loads to the supports, or an initial design domain that fits within the maximum allowable domain, and the optimal topology evolves by adding or subtracting elements. But the convergence rate of BESO is also very slow. In this paper, a new element removal method for ESO was developed for improvement of the convergence rate. Then it was applied to the same problems as those in papers published previously. From the results, it was verified that the convergence rate was significantly improved compared with ESO as well as BESO.

• Structural Engineering and Mechanics
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• 제62권5호
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• pp.537-550
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• 2017

Structural sizing is a rewarding task due to its non-convex constrained nature in the design space. In order to provide both global exploration and proper search refinement, a hybrid method is developed here based on outstanding features of Evolutionary Computing and Teaching-Learning-Based Optimization. The new method introduces an observer phase for memory exploitation in addition to vector-sum movements in the original teacher and learner phases. Proper integer coding is suited and applied for structural size optimization together with a fly-to-boundary technique and an elitism strategy. Performance of the proposed method is further evaluated treating a number of truss examples compared with teaching-learning-based optimization. The results show enhanced capability of the method in efficient and stable convergence toward the optimum and effective capturing of high quality solutions in discrete structural sizing problems.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1996년도 가을 학술발표회 논문집
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• pp.113-120
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• 1996

This study presents the optimization technique to determine the cable areas of the cable-stayed bridge. The optimization method presented in this paper is based on an evolutionary procedure, in which the area of high stressed cable is increased step-by-step until an optimal area of the cable is obtained. A comparison between the maximum values of the present method and those of the cable-stayed bridge that has the same cable area shows the advantages of the present method.

• Structural Engineering and Mechanics
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• 제34권5호
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• pp.581-595
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• 2010

This paper presents topology optimization of geometrically and materially nonlinear structures using a bi-directional evolutionary optimization (BESO) method. To maximum the stiffness of nonlinear structures under prescribed design load, the complementary work is selected as the objective function of the optimization. An optimal design can be obtained by gradually removing inefficient material and adding efficient ones. The proposed method can be applied to a series of geometrically and/or materially nonlinear structures. The results show considerable differences in topologies and stiffness of the optimal designs for linear and nonlinear structures. It is found that the optimal designs for nonlinear structures are much stiffer than those for linear structures when large design loads (which result in significantly nonlinear deformations) are applied.

• Structural Engineering and Mechanics
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• 제81권3호
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• pp.267-280
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• 2022

Multiscale structure has attracted significant interest due to its high stiffness/strength to weight ratios and multifunctional performance. However, most of the existing concurrent topology optimization works are carried out under deterministic load conditions. Hence, this paper proposes a robust concurrent topology optimization method based on the bidirectional evolutionary structural optimization (BESO) method for the design of structures composed of periodic microstructures subjected to uncertain dynamic loads. The robust objective function is defined as the weighted sum of the mean and standard deviation of the module of dynamic structural compliance with constraints are imposed to both macro- and microscale structure volume fractions. The polynomial chaos expansion (PCE) method is used to quantify and propagate load uncertainty to evaluate the objective function. The effective properties of microstructure is evaluated by the numerical homogenization method. To release the computation burden, the decoupled sensitivity analysis method is proposed for microscale design variables. The proposed method is a non-intrusive method, and it can be conveniently extended to many topology optimization problems with other distributions. Several numerical examples are used to validate the effectiveness of the proposed robust concurrent topology optimization method.

• Structural Engineering and Mechanics
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• 제7권5호
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• pp.447-456
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• 1999

This paper presents a solution method, which can be regarded as the further extension of the generalized evolutionary method (Zhao et al. 1998a), for the simultaneous optimization of several different natural frequencies of a structure in general and a two dimensional structure in particular. The main function of the present method is to optimize the topology of a structure so as to simultaneously make several different natural frequencies of interest to be of the corresponding different desired values for the target structure. In order to develop the present method, the new contribution factor of an element is proposed to consider the contribution of an element to the gaps between the currently calculated values for the different natural frequencies of interest and their corresponding desired values in a weighted manner. Using this new contribution factor of an element, the most inefficiently used material can be detected and removed gradually from the design domain of a structure. Through applying the present method to optimize two and three different natural frequencies of a two dimensional structure, it has been demonstrated that it is possible and applicable to use the generalized evolutionary method for tackling the simultaneous optimization of several different natural frequencies of a structure in the structural design.

• 한국전산구조공학회논문집
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• 제24권3호
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• pp.319-328
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• 2011

이 논문은 ESO 기법을 기초로 한 Strut-Tie 모델의 구성을 제안하고 있다. 평면응력 요소를 사용한 기존의 ESO방법과 달리, ESO기법에 의해 최적화된 구조가 트러스와 비슷한 형태를 가지는 사실에 기인하여, Strut-Tie 모델을 통한 전단설계에 트러스 요소를 사용한 ESO기법을 새롭게 적용하였다. 예제들을 통해 제안된 방법이 가장 좋은 Strut-Tie 모델을 찾을 수 있음을 입증하였으며, 앞서 2차원 평면응력 요소와 Strut-Tie 모델의 연관성에 대한 연구를 통해 ESO방법이 효과적으로 사용될 수 있음은 물론 경험하지 못한 특히 복잡한 철근 콘크리트 구조물의 전단설계에 효과적으로 사용이 가능한 대안이 될 수 있을 것으로 판단된다.