• Computational Structural Engineering : An International Journal
• /
• v.1 no.1
• /
• pp.21-29
• /
• 2001

The general topology optimization can be considered as optimal material distribution. Such an approach can be unstable, unless composite materials are introduced. In this research, a nodal volume fraction method is used to obtain the optimum topology of continuum structures. This method is conducted from a composite material model composed of isotropic matter and spherical void. Because the appearance of the chessboard patterns makes the interpretation of the optimal material layout very difficult, this method contains a chessboard prevention strategy. In this research, several topology optimization problems are presented to demonstrate the validity of the present method and the recursive quadratic programming algorithm is used to solve the topology optimization problems.

• Steel and Composite Structures
• /
• v.22 no.4
• /
• pp.733-744
• /
• 2016

In this study, optimum structural designs of braced (non-swaying) planar steel frames are investigated by using one of the recent meta-heuristic search techniques, teaching-learning based optimization. Optimum design problems are performed according to American Institute of Steel Construction- Allowable Stress Design (AISC-ASD) specifications. A computer program is developed in MATLAB interacting with SAP2000 OAPI (Open Application Programming Interface) to conduct optimization procedures. Optimum cross sections are selected from a specified list of 128W profiles taken from AISC. Two different braced planar frames taken from literature are carried out for stress, geometric size, displacement and inter-storey drift constraints. It is concluded that teaching-learning based optimization presents robust and applicable optimum solutions in multi-element structural problems.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.419-424
• /
• 1999

In this paper, the comparison of the first order approximation schemes such as SLP (sequential linear programming), CONLIN(convex linearization), MMA(method of moving asymptotes) and the second order approximation scheme, SQP(sequential quadratic programming) was accomplished for optimization of and nonlinear structures. It was found that MMA and SQP(sequential quadratic programming) was accomplished for optimization of and nonlinear structures. It was found that MMA and SQP are the most efficient methods for optimization. But the number of function call of SQP is much more than that of MMA. Therefore, when it is considered with the expense of computation, MMA is more efficient than SQP. In order to examine the efficiency of MMA for complex optimization problem, it was applied to the helicopter tail boom considering column buckling and local wall buckling constraints. It is concluded that MMA can be a very efficient approximation scheme from simple problems to complex problems.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.31 no.2 s.257
• /
• pp.269-276
• /
• 2007

Optimal thickness and shape of the pedal arm of an automotive clutch is determined, using the numerical optimization technique, by solving the size and shape optimization problems to minimize its weight. For the optimization problems, two cases of stress and displacement constraints are considered: one from the vertical, and the other from the transverse stiffness test condition. The result of the transverse case is shown to be more conservative than that from the vertical case, being determined as the final optimum.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.34C no.12
• /
• pp.61-69
• /
• 1997

This paper proposes a new method for improving the performances of the neural network for optimization using a hyubrid of gradient descent method and dynamic tunneling system. The update rule of gradient descent method, which has the fast convergence characteristic, is applied for high-speed optimization. The update rule of dynamic tunneling system, which is the deterministic method with a tunneling phenomenon, is applied for global optimization. Having converged to the for escaping the local minima by applying the dynamic tunneling system. The proposed method has been applied to the travelling salesman problems and the optimal task partition problems to evaluate to that of hopfield model using the update rule of gradient descent method.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.23 no.6
• /
• pp.683-691
• /
• 2010

In this paper, using an adjoint variable method, we develop a design sensitivity analysis(DSA) method applicable to heat conduction problems in steady state. Also, a topology design optimization method is developed using the developed DSA method. Design sensitivity expressions with respect to the thermal conductivity are derived. Since the already factorized system matrix is utilized to obtain the adjoint solution, the cost for the sensitivity computation is trivial. For the topology design optimization, the design variables are parameterized into normalized bulk material densities. The objective function and constraint are the thermal compliance of structures and allowable material volume respectively. Through several numerical examples, the developed DSA method is verified to yield very accurate sensitivity results compared with finite difference ones, requiring less than 0.25% of CPU time for the finite differencing. Also, the topology optimization yields physical meaningful results.

• Journal of the korean Society of Automotive Engineers
• /
• v.15 no.1
• /
• pp.81-88
• /
• 1993

A direct treatment of the min-max type objective function of the dynamic response optimization problem is proposed. Previously, the min-max type objective function was transformed to an artificial design variable and an additional point-wise state variable constraint function was imposed, which increased the complexity of the optimization problem. Especially, the design sensitivity analysis for the augmented Lagrangian functional with the suggested treatment is established by using the adjoint variable method and a computer program to implement the proposed algorithm is developed. The optimization result of the proposed treatment are obtained for three typical problems and compared with those of the previous treatment. It is concluded that the suggested treatment in much more efficient in the computational effort than the previous treatment with giving the similar optimal solutions.

• Journal of Korean Association for Spatial Structures
• /
• v.24 no.1
• /
• pp.57-64
• /
• 2024

This study numerically compares optimum solutions generated by element- and node-wise topology optimization designs for free vibration structures, where element-and node-wise denote the use of element and nodal densities as design parameters, respectively. For static problems optimal solution comparisons of the two types for topology optimization designs have already been introduced by the author and many other researchers, and the static structural design is very common. In dynamic topology optimization problems the objective is in general related to maximum Eigenfrequency optimization subject to a given material limit since structures with a high fundamental frequency tend to be reasonable stiff for static loads. Numerical applications topologically maximizing the first natural Eigenfrequency verify the difference of solutions between element-and node-wise topology optimum designs.

• 한국전산유체공학회:학술대회논문집
• /
• 2000.05a
• /
• pp.159-165
• /
• 2000

In this paper, numerical study has been done for the improvement of the superdetonative ram accelerator performance and for the design optimization of the system. The objective function to optimize the premixture composition is the ram tube length required to accelerate projectile from initial velocity $V_o$ to target velocity $V_e$. The premixture is composed of $H_2,\;O_2,\;N_2$ and the mole numbers of these species are selected at design variables. RSM(Response Surface Methodology) which is widely used for the complex optimization problems is selected as the optimization technique. In particular, to improve the non-linearity of the response and to consider the accuracy and efficiency of the solution, design space stretching technique has been applied. Separate sub-optimization routine is introduced to determine the stretching position and clustering parameters which construct the optimum regression model. Two step optimization technique has been applied to obtain the optimal system. With the application of stretching technique, we can perform system optimization with a small number of experimental points, and construct precise regression model for highly non-linear domain. The error to compared with analysis result is only $0.01\%$ and it is demonstrated that present method can be applied more practical design optimization problems with many design variables.

• Structural Engineering and Mechanics
• /
• v.66 no.4
• /
• pp.465-476
• /
• 2018

In this paper, a new meta-heuristic optimization method is presented. This new method is named "Numbers Cup Optimization" (NCO). The NCO algorithm is inspired by the sport competitions. In this method, the objective function and the design variables are defined as the team and the team members, respectively. Similar to all cups, teams are arranged in groups and the competitions are performed in each group, separately. The best team in each group is determined by the minimum or maximum value of the objective function. The best teams would be allowed to the next round of the cup, by accomplishing minor changes. These teams get grouped again. This process continues until two teams arrive the final and the champion of the Numbers Cup would be identified. In this algorithm, the next cups (same iterations) will be repeated by the improvement of players' performance. To illustrate the capabilities of the proposed method, some standard functions were selected to optimize. Also, size optimization of three benchmark trusses is performed to test the efficiency of the NCO approach. The results obtained from this study, well illustrate the ability of the NCO in solving the optimization problems.