• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.555-556
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• 2014

In this paper, topology optimization of two-dimensional acoustic lenses is presented by using the phase field method. The objective of the optimization is to maximize the acoustic pressure at a specified domain inside the acoustic domain for a given frequency, and the constraint is imposed on the amount of the material of the acoustic lens. Topology optimization of two-dimensional acoustic lenses are obtained as the steady state of the phase transition described by the Allen-Cahn equation. The Helmholtz equation modeling the wave propagation is solved by using a finite element method. The effectiveness of the proposed method is verified by applying it for several two-dimensional acoustic lens system design problems.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.488-494
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• 2008

This paper proposes an effective approach based on binary coding Particle Swarm Optimization (PSO) to identify the switching operation plan for feeder reconfiguration. The proposed method considers the advantages and disadvantages of existing particle swarm optimization method and redefined the operators of PSO algorithm to fit the application field of distribution systems. Shift operator is proposed to construct the binary coding particle swarm optimization for feeder reconfiguration. A typical distribution system of Taiwan Power Company is used in this paper to demonstrate the effectiveness of the proposed method. The test results show that the proposed method can apply to feeder reconfiguration problems more effectively and stably than existing method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.263-270
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• 2002

This study proposes a multi-objective optimum design method for a rational optimization of high-speed railway bridges. This multi-objective optimization is found to be effective in optimizing multi-objective problems that incorporate cost and dynamic responses such as vertical acceleration and displacement. These design factors are so important in the high-speed railway bridges. And the trade off method which is one of the most typical multi-objective optimization methods is used in this study, since the dynamic factors are formulated as objective function and also considered as constraints. And the Pareto curve can be obtained by performing the multi-objective optimization for real high-speed railway bridges. Thus, it is found that more reasonable design can be obtained when compared with those using conventional design procedure.

• Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.165-175
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• 2015

One of the current challenges in the domain of the multicriteria shape optimization is to reduce the calculation time required by conventional methods. The high computational cost is due to the high number of simulation or function calls required by these methods. Recently, several studies have been led to overcome this problem by integrating a metamodel in the overall optimization loop. In this paper, we perform a coupling between the Normal Boundary Intersection - NBI - algorithm with Radial Basis Function - RBF - metamodel in order to have a simple tool with a reasonable calculation time to solve multicriteria optimization problems. First, we apply our approach to academic test cases. Then, we validate our method against an industrial case, namely, shape optimization of the bottom of an aerosol can undergoing nonlinear elasto-plastic deformation. Then, in order to select solutions among the Pareto efficient ones, we use the same surrogate approach to implement a method to compute Nash and Kalai-Smorodinsky equilibria.

• Korean Journal of Computational Design and Engineering
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• v.10 no.5
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• pp.349-355
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• 2005

This paper concerns about how and why design frameworks for optimization should consider various software development environments such as MATLAB, VB, VBscript, Python, Tcl, PHP, Perl, and JAVA. The frameworks can be utilized by many engineers who have a basic concept about the optimization theory and/or basic knowledge about the computer programming languages. The framework will integrate a number of remote CAE tools, automatically execute them for design optimization, and have the capabilities of post-processing of data such as objective functions, state variables and design variables using a third-party spreadsheet program like Excel. The prototype framework developed in this study will be applied to various examples of optimization problems and show the validity of the proposed method of a framework implemenation.

• IE interfaces
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• v.25 no.2
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• pp.153-162
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• 2012

The reliability is defined as a probability that a system will operate properly for a specified period of time under the design operating conditions without failure and it has been considered as one of the major design parameters in the field of industries. Reliability-Redundancy Optimization Problem(RROP) involves selec tion of components with multiple choices and redundancy levels for maximizing system reliability with constraints such as cost, weight, etc. However, in practice both active and cold standby redundancies may be used within a particular system design. Therefore, a redundancy strategy(active, cold standby) for each subsystem in order to maximize system reliability is considered in this study. Due to the nature of RROP, i.e. NP-hard problem, A Parallel Particle Swarm Optimization(PPSO) algorithm is proposed to solve the mathematical programming model and it gives consistently better quality solutions than existing studies for benchmark problems.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.3-7
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• 1997

Simulation is commonly used to find the best values of decision variables for problems which defy analytical solutions. "Simulation Optimization" technique is used to optimize the expressed in analytical of mathematical models. In this research, we will study Reverse-Simulation optimization method which is quite different from current simulation optimization methods in literature. We will focus on the on-line determination of steady-state method which is very important issue in Reverse-Simulation optimization, and the construction of Reverse-Simulation algorithm with expert systems. Especially, in the case of multiple objectives because of the dependency of simulation model, all objectives do not satisfied simulataneously. In this paper, therefore, we process simulation optimization using objectives with priority to optimize multiple objectives under single run.ingle run.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.335-342
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• 2002

A continuum-based design sensitivity analysis (DSA) method fur non-shape problems is developed for geometrically nonlinear elastic structures. The non-shape problem is characterized by the design variables that are not associated with the domain of system like sizing, material property, loading, and so on. Total Lagrangian formulation with the Green-Lagrange strain and the second Piola-Kirchhoff stress is employed to describe the geometrically nonlinear structures. The spatial domain is discretized using the 4-node isoparametric plane stress/strain elements. The resulting nonlinear system is solved using the Newton-Raphson iterative method. To take advantage of the derived analytical sensitivity In topology optimization, a fast and efficient design sensitivity analysis method, adjoint variable method, is employed and the material property of each element is selected as non-shape design variable. Combining the design sensitivity analysis method and a gradient-based design optimization algorithm, an automated design optimization method is developed. The comparison of the analytical sensitivity with the finite difference results shows excellent agreement. Also application to the topology design optimization problem suggests a very good insight for the layout design.

• Smart Structures and Systems
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• v.21 no.3
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• pp.263-278
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• 2018

Thermal Exchange Optimization (TEO) is a newly developed algorithm which mimics the thermal exchange between a solid object and its surrounding fluid. In this paper, an improved version of the TEO is developed to fix the shortcomings of the standard version. To demonstrate the viability of the new algorithm, the CEC 2016's single objective problems are considered along with the discrete size optimization of benchmark skeletal structures. Problem specific constraints are handled using a fly-back mechanism. The results show the validity of the improved TEO method compared to its standard version and a number of well-known algorithms.

• Journal of Mechanical Science and Technology
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• v.20 no.8
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• pp.1169-1182
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• 2006

Robust design technology has been applied to versatile engineering problems to ensure consistency in product performance. Since 1980s, the concept of robust design has been introduced to numerical optimization field, which is called the robust optimization. The robustness in the robust optimization is determined by a measure of insensitiveness with respect to the variation of a response. However, there are significant difficulties associated with the calculation of variations represented as its mean and variance. To overcome the current limitation, this research presents an implementation of the approximate statistical moment method based on kriging metamodel. Two sampling methods are simultaneously utilized to obtain the sequential surrogate model of a response. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method. Then, the simulated annealing algorithm of global optimization methods is adopted to find the global robust optimum. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.