• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.215-221
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• 1997

A new approach in solving design centering problem is presented. Like most stochastic optimization problems, optimal design centering problems have intrinsic difficulties in multivariate intergration of probability density functions. In order to avoid to avoid those difficulties, genetic algorithm and very coarse Monte Carlo simulation are used in this research. The new algorithm performs robustly while producing improved yields. This result implies that the combination of robust optimization methods and approximated simulation schemes would give promising ways for many stochastic optimizations which are inappropriate for mathematical programming.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.11
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• pp.1297-1308
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• 2011

The light-weight design of UTM (Urban Transit Maglev)-02 car-body frames are performed, based on initial configuration. The thicknesses of fourteen sub-structures are defined as design variables and the loading condition is considered according to weight of sub-structures, electronic and pneumatic modules and passengers. For efficient and robust process of design optimization, objective function and constraints are approximated by response surface approximation. Structural analysis is performed at some sampling points to construct the approximated objective function and constraints composed of design variables. Design space is changed to find many optimal candidates and best optimal design can be found eventually. The Matlab Optimization Toolbox is used to find optimal value and sensitivity analysis about each design variable is also performed.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.12
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• pp.638-644
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• 2017

Optimal cooling operation algorithm was developed based on a simulation case of a single family house model equipped with renewable energy facility. EnergyPlus simulation results were used as virtual test data. The model contained three energy storage elements: thermal heat capacity of the living room, chilled water storage tank, and battery. Their charging and discharging schedules were optimized so that daily electricity bill became minimal. As an optimization tool, linear programming was considered because it was possible to obtain results in real time. For its adoption, EnergyPlus-based house model had to be linearly approximated. Results of this study revealed that dynamic cooling load of the living room could be approximated by a linear RC model. Scheduling based on the linear programming was then compared to that by a nonlinear optimization algorithm which was made using GenOpt developed by a national lab in USA. They showed quite similar performances. Therefore, linear programming can be a practical solution to optimal operation scheduling if linear dynamic models are tuned to simulate their real equivalents with reasonable accuracy.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.11
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• pp.771-781
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• 2022

Sequential convex programming based performance analysis of the designed UAV is performed. The nonlinear optimization problems generated by aerodynamics are approximated to socond order program by discretization and convexification. To improve the performance of the algorithm, the solution of the relaxed problem is used as the initial trajectory. Dive trajectory optimization problem is analyzed through iterative solution procedure of approximated problem. Finally, the maximum final velocity according to the performance of the actuator model was compared.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.14 no.3
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• pp.339-348
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• 2001

More often a commercial package for the structural analysis is necessary in the structural optimum design. In this case the task of combining the package with an optimization program must be required, hut it is not so simple because interchanging some data between them is difficult. Sequential approximate optimization is currently used as a natural way to overcome the hard task. If sequential approximate optimization has wide side constraints that the lower limit of design variables is very small and their upper limit is very large, it is not so easy to obtain approximated functions accurately for the whole design domain. This paper proposes a sequential design domain method, which is very useful to carry out sequential approximate optimization in this case. In this paper, the response surface methodology is used to obtain approximated functions and the orthogonal array is used for design of experiments. The sequential approximate optimization of 3-bar and 10-bar trusses is demonstrated to verify the reliability of the sequential design domain method.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.1
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• pp.112-121
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• 2009

This paper deals with supersonic air-breathing missile system. A supersonic air-breathing missile system has very complicated and incoherent thrust characteristics with respect to outer and inner environment during operation. For this reason, the missile system has many maneuver constraints and is allowed to operate within narrow flight envelope. In this paper, trajectory optimization of the missile is accomplished. The trajectory optimization problem is formulated as a discrete parameter optimization problem. For this formulation, Legendre Pseudo-Spectral method is introduced. This method is based on calculating the state and control variables on Legendre-Gauss-Lobatto (LGL) points. This approach helps to find approximated derivative and integration quantities simply. It is shown that, for this trajectory optimization, trend analysis is performed from thrust characteristics on various conditions so that the trajectory optimization is accomplished with fine initial guess with these results.

• Steel and Composite Structures
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• v.15 no.4
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• pp.451-466
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• 2013

This paper deals with the multi-objective optimization of tire reinforcement structures such as the tread belt and the carcass path. The multi-objective functions are defined in terms of the discrete-type design variables and approximated by artificial neutral network, and the sensitivity analyses of these functions are replaced with the iterative genetic evolution. The multi-objective optimization algorithm introduced in this paper is not only highly CPU-time-efficient but it can also be applicable to other multi-objective optimization problems in which the objective function, the design variables and the constraints are not continuous but discrete. Through the illustrative numerical experiments, the fiber-reinforced tire belt structure is optimally tailored. The proposed multi-objective optimization algorithm is not limited to the tire reinforcement structure, but it can be applicable to the generalized multi-objective structural optimization problems in various engineering applications.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.741-743
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• 2003

A reliability-based topology optimization (RBTO) for electromagnetic systems using the finite element method is presented. Permeability and applied current density are considered as uncertain variable. In order to compute reliability constraints, performance measure approach is used. To find the reliability index, the limit state function is linearly approximated at each iteration. Numerical examples show the effectiveness of the proposed method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.166-171
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• 2004

In this study, shape optimization of micro-static mixer with a cantilever beam was accomplished for mixing the mixing efficiency by using successive response surface approximations. Variables were chosen as the length of cantilever beam and the angle between horizontal and the cantilever beam. Sequential approximate optimization method was used to deal with both highly nonlinear and non-smooth characteristics of flow field in a micro-static mixer. Shape optimization problem of a micro-static mixer can be divided into a series of simple subproblems. Approximation to solve the subproblems was performed by response surface approximation, which does not require the sensitivity analysis. To verify the reliability of approximated objective function and the accuracy of it, ANOVA analysis and variables selection method were implemented, respectively. It was verified that successive response surface approximation worked very well and the mixing efficiency was improved very much comparing with the initial shape of a micro-static mixer.

• Structural Engineering and Mechanics
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• v.3 no.4
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• pp.359-372
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• 1995

This study presents an efficient method for optimum design of plate and shell structures, when the design variables are continuous or discrete. Both sizing and shape design variables are considered. First the structural responses such as element forces are approximated in terms of some intermediate variables. By substituting these approximate relations into the original design problem, an explicit nonlinear approximate design task with high quality approximation is achieved. This problem with continuous variables, can be solved by means of numerical optimization techniques very efficiently, the results of which are then used for discrete variable optimization. Now, the approximate problem is converted into a sequence of second level approximation problems of separable form and each of which is solved by a dual strategy with discrete design variables. The approach is efficient in terms of the number of required structural analyses, as well as the overall computational cost of optimization. Examples are offered and compared with other methods to demonstrate the features of the proposed method.