• Journal of computational fluids engineering
• /
• v.11 no.1 s.32
• /
• pp.21-28
• /
• 2006

Reliability Based Design Optimization(RBDO) is one of the optimization methods that minimize the product failure due to small changes of operating conditions or process errors. It searches the optimum that satisfies the safety margin of each constraint, and it gives stable and reliable designs. However, RBDO requires many times oj computational efforts compared with the conventional deterministic optimization(DO) to evaluate the probability of failure about each constraint, therefore it is hard to apply directly to large-scaled problems such as a flexible wing shape design optimization. For the efficient reliability analysis, the approximate reliability analysis method with the two-point approximation(TPA) is proposed In this study, the lift-to-drag ratio maximization designs are performed with 3-dimensional Navier-Stokes analysis and NASTRAN structural analysis, and the optimization results about the deterministic, FORM and SORM are compared.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.29 no.7 s.238
• /
• pp.1013-1021
• /
• 2005

In this paper, we developed an automatic design optimization system for parametric shape optimization of cooling passages inside axial turbine blades. A parallel three-dimensional thermoelasticity finite element analysis code from an open source system was used to perform automatic thermal and stress analysis of different blade configuration. The developed code was connected to an evolutionary optimizer and built in a design optimization system. Using the optimization system, 279 feasible and optimal solutions were searched. It is provided not only one best solution of the searched solutions, but also information of variation structure and correlation of the 279 solutions in function, variable, and real design spaces. To explore design information, it is proposed a new interpretation approach based on evolutionary clustering and principal component analysis. The interpretation approach might be applicable to the increasing demands in the general area of design optimization.

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.1156-1161
• /
• 2008

Nonlinear dynamic analysis is generally used in automobile crash analysis and structural optimization considering crashworthiness uses the results of nonlinear dynamic analysis. Automobile crash optimization has high nonlinearity and difficulty in calculating sensitivity. Recently the equivalent static load (ESL) method has been proposed in order to overcome these difficulties. The ESL is the static load set generating the same displacement field as the nonlinear dynamic displacement field at each time step in dynamic analysis. From various researches regarding the ESL method, it has been proved that the ESL method is fairly useful. The ESL method can mathematically optimize a crash optimization problem through nonlinear analysis and well developed static optimization. The ESL is applied to nonlinear dynamic structural optimization of the automobile frontal impact problem. An automobile bumper is optimized. The mass of the structure is minimized while some constraints are satisfied.

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.412-417
• /
• 2008

In a traditional topology optimization method, material properties are usually distributed by finite element density and visualized by a gray level image. The distribution method based on element density is adequate for a great mass of 2-D topology optimization problems. However, when it is used for 3-D topology optimization, it is always difficult to obtain a smooth model representation, and easily appears a virtualconnect phenomenon especially in a low-density domain. The 3-D structural topology optimization method has been developed using the node density instead of the element density that is based on SIMP (solid isotropic microstructure with penalization) algorithm. A computer code based on Matlab was written to validate the proposed method. When it was compared to the element density as design variable, this method could get a more uniform density distribution. To show the usefulness of this method, several typical examples of structure topology optimization are presented.

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

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.13 no.2
• /
• pp.81-87
• /
• 2004

This paper deals with a new approach to tolerance optimization problems. Optimal tolerance allotment problems can be formulated as stochastic optimization problems. Most schemes to solve the stochastic optimization problems have been found to exhibit difficulties in multivariate integration of the probability density function. As a typical example of stochastic optimization the optimal tolerance allotment problem has the same difficulties. In this stochastic model, manufacturing system is represented by Gauss-Markov stochastic process and the manufacturing unit availability is characterized for realistic optimization modeling. The new algorithm performed robustly for a large deviation approximation. A significant reduction in computation time was observed compared to the results obtained in previous studies.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.21 no.1
• /
• pp.30-38
• /
• 2013

This paper describes the design optimization of Unmanned Aerial Vehicles(UAVs). An optimization framework has been developed and implemented for the conceptual design of UAVs. An integrated design analysis program was developed with several analysis modules such as propulsion, performance, mission, weight, and stability and control. A UAV configuration design optimization was performed by implementing the integrated analysis to enhance the endurance of UAVs. A SQP optimizer was utilized to build an optimization module for this program and sensitivity analysis was performed to determine the trends of shape variables for developing optimization objective. In conclusion, the results indicate that the resulting optimized UAVs configurations show performance improvements over the baseline design and reliable analysis results.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2005.10a
• /
• pp.277-280
• /
• 2005

A shape optimization is applied to achieve a design objective in three-dimensional forging processes. In multi-stage forging processes, among the important design aspects, the die shape fur preforming is regarded as the design variable since it influences the forged part relatively higher than the others. The rigid-plastic finite element method and the sensitivity method are employed and formulated to solve a formulated optimization problem. An approximation scheme is also used for the direction search during the optimization. The upset forging of a square box is selected as a test example in order to demonstrate and verify the optimization process of this study. After the optimization, the optimized shape of the die yields a finial product of desire shape.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.12
• /
• pp.75-82
• /
• 2015

Generally, the optimal solution of assignment problem can be obtained by Hungarian algorithm of two-sided optimization with time complexity $O(n^4)$. This paper suggests one-sided optimal assignment and swap optimization algorithm with time complexity $O(n^2)$ can be achieve the goal of two-sided optimization. This algorithm selects the minimum cost for each row, and reassigns over-assigned to under-assigned cell. Next, that verifies the existence of swap optimization candidates, and swap optimizes with ${\kappa}-opt({\kappa}=2,3)$. For 27 experimental data, the swap-optimization performs only 22% of data, and 78% of data can be get the two-sided optimal result through one-sided optimal result. Also, that can be improves on the solution of best known solution for partial problems.

• Journal of Ubiquitous Convergence Technology
• /
• v.2 no.1
• /
• pp.40-50
• /
• 2008

The problem of assigning customers to satellite channels is a difficult combinatorial optimization problem and is NP-complete. For this combinatorial optimization problem, standard optimization methods take a large computation time and so genetic algorithms (GA) and ant colony optimization (ACO) can be used to obtain the best and/or optimal assignment of customers to satellite channels. In this paper, we present a comparative study of GA and ACO to this problem. Various issues related to genetic algorithms approach to this problem, such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. We also discuss an ACO for this problem. In ACO methodology, three strategies, ACO with only ranking, ACO with only max-min ant system (MMAS), and ACO with both ranking and MMAS, are considered. A comparison of these two approaches (i,e., GA and ACO) with the standard optimization method is presented to show the advantages of these approaches in terms of computation time.