• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1936-1941
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• 2009

This paper deals with a new methodology for topology optimization in which the topology of the design domain may change during the shape optimization process. To achieve this, the concept of the topological gradient is introduced to compute the sensitivity of an objective function when a small hole is drilled in the domain. Based on shape and topological sensitivity values, the shape and topology of the design domain may be simultaneously changed during design iterations if necessary. To verify the advantages and also to facilitate understanding of the method itself, two electrostatic design problems have been tested by using 2D finite element analysis: the first is the inverse problem of a simple dielectric model and the second is the rotor design of a MEMS actuator.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.563-573
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• 2007

Optimal design of an automotive catalytic converter for minimization of cold-start emissions is numerically performed using a micro genetic algorithm for two optimization problems: optimal geometry design of the monolith for various operating conditions and optimal axial catalyst distribution. The optimal design process considered in this study consists of three modules: analysis, optimization, and control. The analysis module is used to evaluate the objective functions with a one-dimensional single channel model and the Romberg integration method. It obtains new design variables from the control module, produces the CO cumulative emissions and the integral value of a catalyst distribution function over the monolith volume, and provides objective function values to the control module. The optimal design variables for minimizing the objective functions are determined by the optimization module using a micro genetic algorithm. The control module manages the optimal design process that mainly takes place in both the analysis and optimization modules.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.425-426
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• 2007

In power systems operation, state estimation takes an important role in security control. For the state estimation problem, conventional optimization algorithm, such as weighted least squares (WLS) method, has been widely used. But these algorithms have disadvantages of converging local optimal solution. In these days, a modern heuristic optimization methods such as Particle Swarm Optimization (PSO), are introducing to overcome the problems of classical optimization. In this paper, we suggested parallel particle swarm optimization (PPSO) to search an optimal solution of state estimation in power systems. To show the usefulness of the proposed method over the conventional PSO, proposed method is applied on the IEEE-57 bus system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.2
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• pp.206-213
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• 2004

In this study, the topology optimization is applied to the design of a piezoelectric microactuator satisfying the specific mean transduction ratio(MTR). The optimization problem is formulated to minimize the difference between the specified and the current mean transduction ratio. In order to analyze the response of the piezoelectric-structure coupled system, both the structural and the electric potential are considered in the finite element method. The optimization problem is resolved by using Sequential Linear Programming(SLP) and the results of test problems show that the design of a piezoelectric microactuator with the specified mean transduction ratio can be obtained.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.4
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• pp.370-377
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• 2004

The density approach and the homogenization design method are representative methods in topology optimization problems. In the topology optimization in magnetic fields, those methods are applied based on the results of the applications In elastic fields. In this study, the density method is modified considering the concept of the homogenization design method. Also, the results of the topology optimization in magnetic fields by the modified density method as well as the homogenization method are compared especially focusing the change of the penalization parameter in the density approach. The effect of the definition of the design domain such as global/local design domain is also discussed.

• Structural Engineering and Mechanics
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• v.60 no.6
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• pp.1093-1117
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• 2016

Global sensitivity analysis (GSA) has been widely used to investigate the sensitivity of the model output with respect to its input parameters. In this paper a new single-solution search optimization algorithm is developed based on the GSA, and applied to the size optimization of truss structures. In this method the search space of the optimization is determined using the sensitivity indicator of variables. Unlike the common meta-heuristic algorithms, where all the variables are simultaneously changed in the optimization process, in this approach the sensitive variables of solution are iteratively changed more rapidly than the less sensitive ones in the search space. Comparisons of the present results with those of some previous population-based meta-heuristic algorithms demonstrate its capability, especially for decreasing the number of fitness functions evaluations, in solving the presented benchmark problems.

• Computers and Concrete
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• v.24 no.2
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• pp.117-123
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• 2019

Optimization is an important subject which is widely used in engineering problems. In this paper, an analytical method is developed for optimum design of reinforced concrete beams considering both flexural and shear effects. A closed-form formulation is derived for optimal height and rebar of beams. The total material cost of steel and concrete is considered as the objective function which is minimized during the optimization process. The ultimate flexural and shear capacities of the beam are considered as the main constraints. The ultimate limit state is considered for deriving the relations for flexural capacity of the beam. The design requirements are considered according to the item 9 of the Iranian National Building. Analytical formulas and some curves are proposed to be used for optimum design of RC beams. The proposed method can be used to perform the optimization of RC beams without the need of any prior knowledge in optimization. Also, the results of the studied numerical example show that the proposed method results in a better design comparing with the other methods.

• Journal of Korean Association for Spatial Structures
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• v.21 no.2
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• pp.89-97
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• 2021

This paper describes an adaptive hybrid evolutionary firefly algorithm for a topology optimization of truss structures. The truss topology optimization problems begins with a ground structure which is composed of all possible nodes and members. The optimization process aims to find the optimum layout of the truss members. The hybrid metaheuristics are then used to minimize the objective functions subjected to static or dynamic constraints. Several numerical examples are examined for the validity of the present method. The performance results are compared with those of other metaheuristic algorithms.

• Coupled systems mechanics
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• v.11 no.3
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• pp.259-266
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• 2022

Non-Traditional Optimization methods are successfully used in solving many engineering problems. Shaft is one of important element of machines and it is used to transmit power from a machine which produces power to a machine which absorbs power. In this paper, ten non-traditional optimization methods that are ALO, GWO, DA, FPA, FA, WOA, CSO, PSO, BA and GSA are used to find minimum weight of hollow shaft to get global optimal solution. The problem has two design variables and two inequality constraints. The comparative results show that the Particle Swarm Optimization outperforms other methods and the results are validated using ANSYS.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.701-711
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• 2019

Purpose: The problem of optimizing redundancy allocation in multi-level systems is considered when each item in a multi-level system has alternative items with the same function. The number of redundancy of multi-level system is allocated to maximize the reliability of the system under path set and cost limitation constraints. Methods: Based on cost limitation and path set constraints, a mathematical model is established to maximize system reliability. Particle swarm optimization is employed for redundant allocation and verified by numerical experiments. Results: Comparing the particle swarm optimization method and the memetic algorithm for the 3 and 4 level systems, the particle swarm optimization method showed better performance for solution quality and search time. Particularly, the particle swarm optimization showed much less than the memetic algorithm for variation of results. Conclusion: The proposed particle swarm optimization considerably shortens the time to search for a feasible solution in MRAP with path set constraints. PS optimization is expected to reduce search time and propose the better solution for various problems related to MRAP.