• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.377-390
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• 2011

A common problem encountered in product or process design is the selection of optimal parameter levels which involves simultaneous consideration of multiple response variables. This is called a multiresponse problem. A multiresponse problem is solved through three major stages: data collection, model building, and optimization. Up to date, various methods have been proposed for the optimization, including the desirability function approach and loss function approach. In this paper, the existing studies in multiresponse optimization are reviewed and a future research direction is then proposed.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.593-609
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• 2004

Peak response is a more suitable index than mean response in the light of structural safety. In this study, a controller optimization method is proposed to restrict peak responses of building structures subject to earthquake excitations, which are modeled as partially stationary stochastic process. The constraints are given with specified failure probabilities of peak responses. LQR is chosen to assure stability in numerical process of optimization. Optimization problem is formulated with weightings on controlled outputs as design variables and gradients of objective and constraint functions are derived. Full state feedback controllers designed by the proposed method satisfy various design objectives and output feedback controllers using LQG also yield similar results without significant performance deterioration.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.330-335
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• 2012

The shape optimization of a Thomson coil actuator used in an arc eliminator is done for fast response by adopting topology modification method. The displacement of the plate in a fixed calculation time is taken as the objective function. The objective function and contribution factor are calculated by using an adaptive equivalent circuit method which has been proved accurate and efficient. Both shape optimization and performance analysis are accomplished based on the segmentation of plate. Through the refinement of the sensitive segments a precise optimal plate shape can be obtained. The effectiveness of the proposed method is proved by the comparison of results before and after the shape optimization.

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.58-63
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• 2012

The shape optimization of a Thomson coil actuator used in an arc eliminator is done for fast response by adopting topology modification method. The displacement of the plate in a fixed calculation time is taken as the objective function. The objective function and contribution factor are calculated by using an adaptive equivalent circuit method which has been proved accurate and efficient. Both shape optimization and performance analysis are accomplished based on the segmentation of plate. Through the refinement of the sensitive segments a precise optimal plate shape can be obtained. The effectiveness of the proposed method is proved by the comparison of results before and after the shape optimization.

• 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.

• International Journal of Automotive Technology
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• v.4 no.3
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• pp.135-140
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• 2003

In the deterministic optimization of a structural system, objective function, design constraints and design variables, are treated in a nonstatistical fashion. However, such deterministic engineering optimization tends to promote the structural system with lest reliability redundancy than obtained with conventional design procedures using the factor of safety. Consequently, deterministic optimized structures will usually have higher failure probabilities than unoptimized structures. Therefore, a balance must be developed between the satisfactions of the design requirements and the objectives of reducing manufacturing cost. This paper proposes the reliability-based design optimization (RBDO) technique, which enables the optimum design that considers confidence level for the vibration characteristics of structural system. Response surface method (RSM) is utilized to approximate the performance functions describing the system characteristics in the RBDO procedure. The proposed optimization technique is applied to the pillar section design considering natural frequencies of a vehicle structure.

• Steel and Composite Structures
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• v.44 no.2
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• pp.211-224
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• 2022

Multi-objective optimization was conducted to obtain the optimal configuration of a composite sandwich structure with honeycomb-foam hybrid core subjected to underwater shock waves, which can fulfill the demand for light weight and energy efficient design of structures against underwater blast. Effects of structural parameters on the dynamic response of the sandwich structures subjected to underwater shock waves were analyzed numerically, from which the correlations of different parameters to the dynamic response were determined. Multi-objective optimization of the structure subjected to underwater shock waves of which the initial pressure is 30 MPa was conducted based on surrogate modelling method and genetic algorithm. Moreover, optimization results of the sandwich structure subjected to underwater shock waves with different initial pressures were compared. The research can guide the optimal design of composite sandwich structures subjected to underwater shock waves.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.2
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• pp.268-275
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• 2003

Generally, structural optimization is carried out based on external static loads. All forces have dynamic characteristics in the real world. Mathematical optimization with dynamic loads is extremely difficult in a large-scale problem due to the behaviors in the time domain. The dynamic loads are often transformed into static loads by dynamic factors, design codes, and etc. Therefore, the optimization results can give inaccurate solutions. Recently, a systematic transformation has been proposed as an engineering algorithm. Equivalent static loads are made to generate the same displacement field as the one from dynamic loads at each time step of dynamic analysis. Thus, many load cases are used as the multiple leading conditions which are not costly to include in modern structural optimization. In this research, it is mathematically proved that the solution of the algorithm satisfies the Karush-Kuhn-Tucker necessary condition. At first, the solution of the new algorithm is mathematically obtained. Using the termination criteria, it is proved that the solution satisfies the Karush-Kuhn-Tucker necessary condition of the original dynamic response optimization problem. The application of the algorithm is discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.3
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• pp.259-268
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• 2015

An optimization method for the tube hydroforming process is developed using the equivalent static loads method for non linear static response structural optimization (ESLSO). The aims of the tube hydroforming optimization are to determine the axial forces (axial feedings) and the internal pressures, and to obtain the desired shape without failures after hydroforming analysis. Therefore, the magnitude of the forces should be design variables in the optimization process. Also, some tube hydroforming optimization needs to consider the result of the thickness in nonlinear dynamic analysis as responses. However, the external forces are considered as constants and the thickness is not a response in the linear response optimization process of the original ESLSO. Thus, a new ESLSO process is proposed to overcome the difficulties and some examples are solved to validate the proposed method.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.23-34
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• 2023

The purpose of this paper is to review global stochastic optimization algorithms(GSOA) in case binary response experimentation is used and to compare the performances of them. GSOAs utilise estimator of probability of success $\^p$ instead of population probability of success p, since p is unknown and only known by its estimator which has stochastic characteristics. Hill climbing algorithm algorithm, simple random search, random search with random restart, random optimization, simulated annealing and particle swarm algorithm as a population based algorithm are considered as global stochastic optimization algorithms. For the purpose of comparing the algorithms, two types of test functions(one is simple uni-modal the other is complex multi-modal) are proposed and Monte Carlo simulation study is done to measure the performances of the algorithms. All algorithms show similar performances for simple test function. Less greedy algorithms such as Random optimization with Random Restart and Simulated Annealing, Particle Swarm Optimization(PSO) based on population show much better performances for complex multi-modal function.