• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.10a
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• pp.296-303
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• 1996

This paper proposes a method for shape optimization of trusses. The potential savings offered by shape optimization will certainly be more significant than those resulting from fixed-geometry optimization. On the other hand, difficulties associated with topology and geometry optimization are still in existence. Even with a known topology, the geometry optimization problem is still a difficult task. An evolutionary procedure to be adopted and improved in this work, however, offers a means to achieve optimization in topology and geometry together. A plane truss structure is modelled within a specified domain and made to include a great number of nodes and members. Then the structure is analyzed and those members with stresses below a certain level are progressively eliminated from the structural system In this manner the structure evolves into a truss with a better topology and geometry by removing less important parts. Through the worked examples, we can see that the method presented in this Paper shows much promise.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.699-704
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• 2000

The present paper deals with a multiobjective optimization method based on the co-evolutionary genetic strategy. The co-evolutionary strategy carries out the multiobjective optimization in such way that it optimizes individual objective function as compared with each generation's value while there are more than two genetic evolutions at the same time. In this study, the designs that are out of the given constraint map compared with other objective function value are excepted by the penalty. The proposed multiobjective genetic algorithms are distinguished from other optimization methods because it seeks for the optimized value through the simultaneous search without the help of the single-objective values which have to be obtained in advance of the multiobjective designs. The proposed strategy easily applied to well-developed genetic algorithms since it doesn't need any further formulation for the multiobjective optimization. The paper describes the co-evolutionary strategy and compares design results on the simple structural optimization problem.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.6
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• pp.826-833
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• 2010

Electric-thermal-structural actuated compliant mechanisms are mechanisms onto which electric voltage drop is applied as input instead of force. This mechanism is based on thermal expansion of material while being heated. Compliant mechanisms are designed subjected to electric charge input using BESO(bi-directional evolutionary structural optimization) method. Reliability-based topology optimization (RBTO) is applied to the topology design of actuators. performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints. In this study, BESO method is used to obtain optimal topology of compliant mechanisms from initial design domain. PMA approach is used to evaluate reliability index. The procedure has been tested in numerical applications and compared with the results obtained by other methods to validate these approaches.

• Structural Engineering and Mechanics
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• v.4 no.5
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• pp.513-527
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• 1996

In this paper, both an approximate expression and an exact expression for the contribution factor of an element to the natural frequency of the finite element discretized system of a structure in general and a membrane in particular have been derived from the energy conservation principle and the finite element formulation of structural eigenvalue problems. The approximate expression for the contribution factor of an element is used to predict and determine the elements to be removed in an iteration since it depends only on the quantities associated with the old system in the iteration. The exact expression for the contribution factor of an element makes it possible to check whether the element is correctly removed at the end of an iteration because it depends on both the old system and the new system in the iteration. Thus, the combined use of the approximate expression and the exact expression allows a considerable number of elements to be removed in a single iteration so that the efficiency of the evolutionary structural optimization method can be greatly improved for solving the natural frequency optimization problem of a structure. A square membrane with different boundary supports has been chosen to investigate the general evolutionary path for the fundamental natural frequency of the structure. The related results indicated that if the objective of a structural optimization is to raise the fundamental natural frequency of the structure to an optimal value, the general evolutionary path during its optimization is that the elements are gradually removed along the direction from the area surrounded by the contour of the highest value to that surrounded by the contour of the lowest value.

• Journal of Korean Association for Spatial Structures
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• v.3 no.3 s.9
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• pp.67-74
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• 2003

The purpose of this study is to improve convergence speed of topology optimization procedure using the existing ESO method and to deal with topology decision of the truss structures according to a boundary condition, such as cantilever type. At the existing ESO topology optimization procedure for the truss structures, the adjustment of member sizes according to target stress has been executed by increasing or reducing a very small value from each member size. In this case, it takes too much iteration till convergence. Accordingly, it is practically hard to obtain optimum topology for a large scale structures. For that reason, it is necessary to improve convergence speed of ESO method more effectively. During the topology decision procedure, member sizes are adjusted by calculating approximate solution for member sizes corresponding to the target stress at every step, the new member sizes are adjusted by such method are applied in FEA procedure of next step.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.5
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• pp.112-118
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• 2000

In case ESO(evolutionary structural optimization) which is one of topology optimization methods, the element removal ratio is fixed throughout topology optimization by 1 or 2%. As a result it has no flexibility for various types of structures and thus the rate of convergence might not be efficient. Thus various element removal methods were developed in order to improve the efficiency of ESO. In this paper, various element removal methods for ESO are compared with each other for a bracket and a short cantilever. In addition, a new improved bi-directional element removal method is suggested in order to obtain much better optimized topology. From the comparative results of the examples, it is verified that all of the developed various element removal methods are very effective, and the suggested element removal method is the most effective.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.295-302
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• 2002

This paper introduces a method to determine strut-tie models in reinforced concrete (RC) structures using the evolutionary structural optimization (ESO). Even though strut-tie models are broadly adapted in design of reinforced concrete members subjected to shear and torsion, conventional methods can hardly give correct models in RC members subjected to complex loadings and geometry conditions. In this paper, the basic idea of the ESO method is used to determine more rational strut-tie models. Since an optimum topology of structures, finally obtained by the ESO method, usually represents a truss-like structure, the ESO method can effectively be used in finding the best strut-tie model in RC structures. Several example structures are provided to demonstrate the capability of the proposed method in finding the best strut-tie model of each RC structure and to verify its efficiency in application to real design problems.

• Structural Engineering and Mechanics
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• v.65 no.3
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• pp.303-314
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• 2018

Shear walls are a typical member under a complex stress state and have complicated mechanical properties and failure modes. The separated-elements model Genetic Evolutionary Structural Optimization (GESO), which is a combination of an elastic-plastic stress method and an optimization method, has been introduced in the literature for designing such members. Although the separated-elements model GESO method is well recognized due to its stability, feasibility, and economy, its adequacy has not been experimentally verified. This paper seeks to validate the adequacy of the separated-elements model GESO method against experimental data and demonstrate its feasibility and advantages over the traditional elastic stress method. Two types of reinforced concrete shear wall specimens, which had the location of an opening in the middle bottom and the center region, respectively, were utilized for this study. For each type, two specimens were designed using the separated-elements model GESO method and elastic stress method, respectively. All specimens were subjected to a constant vertical load and an incremental lateral load until failure. Test results indicated that the ultimate bearing capacity, failure modes, and main crack types of the shear walls designed using the two methods were similar, but the ductility indexes including the stiffness degradation, deformability, reinforcement yielding, and crack development of the specimens designed using the separated-elements model GESO method were superior to those using the elastic stress method. Additionally, the shear walls designed using the separated-elements model GESO method, had a reinforcement layout which could closely resist the actual critical stress, and thus a reduced amount of steel bars were required for such shear walls.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.752-757
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• 2001

To reduce stress concentration around the intersection between a spherical pressure vessel and a cylindrical nozzle under various load conditions using less material, the optimization for the distribution of reinforcement has researched. The ranked bidirectional evolutionary structural optimization(R-BESO) method is developed recently, 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. In this paper, the optimized intersection shape is sought using R-BESO method for a flush and a protruding nozzle. The considered load cases are a radial compression, torque and shear force.

• Journal of Mechanical Science and Technology
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• v.16 no.4
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• pp.454-467
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• 2002

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. Toidentifythelocation and depth of a crack in a structure, a method is presented in this paper which uses neuro-fuzzy-evolutionary technique, that is, Adaptive-Network-based Fuzzy Inference System (ANFIS) solved via hybrid learning algorithm (the back-propagation gradient descent and the least-squares method) and Continuous Evolutionary Algorithms (CEAs) solving sir ale objective optimization problems with a continuous function and continuous search space efficiently are unified. With this ANFIS and CEAs, it is possible to formulate the inverse problem. ANFIS is used to obtain the input(the location and depth of a crack) - output(the structural Eigenfrequencies) relation of the structural system. CEAs are used to identify the crack location and depth by minimizing the difference from the measured frequencies. We have tried this new idea on beam structures and the results are promising.