• Journal of Ocean Engineering and Technology
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• v.16 no.3
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• pp.28-33
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• 2002

Optimization of marine propellers of constant pitch is studied, with the help of the infinite dimensional optimization (Jang and Kinoshita, 2000a), which is based on the Hilbert space theory. As a numerical example, the MAU type propeller is considered and used as he initial guess for the optimization method. The numerical computations for an optimal marine propeller are performed for the constant pitch distribution. In addition, a new optimization is suggested with the constraint of constant pitch during optimization.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.262-269
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• 2005

Optimization of a satellite structure under severe space launching environments is performed considering various design constraints. Simulate annealing, one of combinatorial optimization techniques, is used to optimize the satellite. The optimization results by the simulated annealing are compared to those by the method of modified feasible direction and genetic algorithm. Ten bar truss structure is optimized for feasibility study of the simulated annealing. Finally, the satellite structure is optimized by the simulated annealing algorithm under space environment. Weights of the satellite upper platform and propulsion module are minimized with consideration of several static and dynamic constraints. MSC/NASTRAN is used to find the static and dynamic responses. Simulated annealing has been programmed and integrated with the finite element analysis program for optimization. It is shown that the simulated annealing algorithm can be extended to the optimization of space structures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.4
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• pp.127-135
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• 1984

This paper considers the problem of optimum shaping of steel arches subjected to general loading. The weight of arches is considered as the objective function and the appropriate combinations of section forces, material volume, arc length, and closed section area of arches are considered as the stress constraints. The shape optimization problems are formulated in terms of the design variables of sectional areas of each element. First the cost sensitivity of the design is investigated. Then the investigation comprises the search for the optimum arch form as well as the optimum area distribution along the arch. Two spaces of shape optimization algorithm will be treated, the first space corresponding to the section optimization by the Modified Newton Raphson Method, and the second space to the coordinate optimization by the Powell Method. The optimization algorithm is evaluated and the optimum span-rise ratios for the given arches are evaluated.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.67-70
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• 1991

When analyzing field or optimizing the shape of electrode in three dimensional space by using the surface charge method, we need to divide finely the surface of electrode into surface element like triangle or rectangle. In this case, there exist any variables in field analysis or field optimization. In particular, smoothness on the surface of optimized shape is not good. Recently, A paper is published where introducing NURB curve to field analysis and field optimization about two dimensional space model and axial symmetric three dimensional space model results in reduced variables, enhenced accuracy and improved smoothness. NURB curve has some useful properties like continuity, controllability and locality. Therefore in this paper, in order to improve the demerits of the established optimization method for three dimensional space models, the NURB surface that has same properties in common with NURB curve is used to analyze and optimize simple model.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1005-1010
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• 2004

The structural optimization has been carried out in the continuous design space or in the discrete design space. Generally, available designs are discrete in design practice. But methods for discrete variables are extremely expensive in computational cost. In order to overcome this weakness, an iterative optimization algorithm was proposed for design in the discrete space, which is called as a sequential algorithm using orthogonal arrays (SOA). We focus to verify the fact that the local solution can be obtained throughout the optimization with this algorithm. The local solution is defined in discrete design space. Then the search space, which is the set of candidate values of each design variables formed by the neighborhood of current design point, is defined. It is verified that a local solution can be founded by moving sequentially the search space. The SOA algorithm has been applied to problems such as truss type structures. Then it is confirmed that a local solution can be obtained using the SOA algorithm

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.6
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• pp.1194-1202
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• 2002

A study on the topology optimization of a multi-spectral camera for space-use is presented. The optimization is carried out under self-weight and polishing pressure loading. A multi-spectral camera for space-use experiences degradation of optical image in the space, which can not be detected on the optical test bench on the earth. An optical surface deformation of a primary mirror, which is a principal component of the camera system, is an important factor affecting the optical performance of the whole camera system. In this study, topology optimization of the primary mirror of the camera is presented. As an objective function, a measure of Strehl ratio is used. Total mass of the primary mirror is given as a constraint to the optimization problem. The sensitivities of the objective function and constraint are calculated by direct differentiation method. Optimization procedure is carried out by an optimality criteria method. For the light-weight primary mirror design, a three dimensional model is treated. As a preliminary example, topology optimization considering a self-weight loading is treated. In the second example, the polishing pressure is also included as a loading in the topology optimization of the mirror. Results of the optimized design topology for the mirror with various mass constraints are presented.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.217.1-217.1
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• 2005

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.780-787
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• 2017

The propellant grain configuration is a design variable that determines the shape and performance of a solid rocket motor. Grain configuration variables have complicated effects on the motor performance; so the global optimization problem has to be solved in order to design the configuration variables. The grain performance has been analyzed by means of the grain burn-back and internal ballistic analysis, and the optimization technique searches for the configuration variables that satisfy the requirements. The deterministic and stochastic optimization techniques have been applied for the grain optimization, but the results are imperfect. In this study, the optimization design of the configuration variables has been performed using the hybrid optimization technique, which combines those two techniques. As a result, the hybrid optimization technique has proved to be efficient for the grain optimization design.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.541-548
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• 2014

In this paper, we introduce a second version of modified binary particle swarm optimization using a concept of genotype-phenotype in genetic algorithms. Particle swarm optimization uses an information of difference between a position of the best solution and one's own position in the process of searching optimum. To obtain this difference of positions, the first version of modified binary particle swarm optimization uses a phenotype but the proposed second version uses a genotype. We can represent the solution space in large search space by using a genotype which provides continuous whole space as search space compared to a phenotype which provides only binary information. Experimental results in 10 De Jong benchmark function show that the second version outperforms the first version in six functions which has a broad search space and many local optima.

• Structural Engineering and Mechanics
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• v.81 no.2
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• pp.195-203
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• 2022

This paper presents the quantification and location damage detection of plane and space truss structures in a two-phase method to reduce the computations efforts significantly. In the first phase, a proposed damage indicator based on the residual force vector concept is used to get the suspected damaged members. In the second phase, using damage quantification as a variable, a teaching-learning based optimization algorithm (TLBO) is used to obtain the damage quantification value of the suspected members obtained in the first phase. TLBO is a relatively modern algorithm that has proved distinguished in solving optimization problems. For more verification of TLBO effeciency, the classical particle swarm optimization (PSO) is used in the second phase to make a comparison between TLBO and PSO algorithms. As it is clear, the first phase reduces the search space in the second phase, leading to considerable reduction in computations efforts. The method is applied on three examples, including plane and space trusses. Results have proved the capability of the proposed method to precisely detect the quantification and location of damage easily with low computational efforts, and the efficiency of TLBO in comparison to the classical PSO.