• Proceedings of the KSME Conference
• /
• 2000.11a
• /
• pp.345-350
• /
• 2000

In this paper, we introduce a new artificial material model for topology optimization. The present material model, named S-shape material model, accelerates topology optimization process especially in mathematical programming. We overcome the instability and the flatness in heuristic optimization process. Numerical examples show the superiority of the proposed material.

• Journal of the Korea Society for Simulation
• /
• v.27 no.2
• /
• pp.83-90
• /
• 2018

This paper describes the method of hull shape optimization to improve the resistance performance of planing hulls when a reference hull shape and its principal dimensions are given. First, the planing hull of precedent research is adopted as the reference hull and an optimization problem is formulated by defining hull shape parameters. The search space of this research is discretized for computing cost and DPSO(Discrete binary version of Particle Swarm Optimization) method is used to solve the optimization problem. As the result of optimization, the decrease of resistance is confirmed from the comparison between the reference hull's and the modified hull's planing performance from computational results.

• Journal of Korean Association for Spatial Structures
• /
• v.10 no.4
• /
• pp.59-66
• /
• 2010

This study presents the topology optimization technique by density method to determine the initial shape of space truss structures. Most initial shape design is performed by designer's previous experiences and trial and error method instead of the application of reasonable optimization method. Thus, the reasonable and economical optimization methods are needed to be introduced for the initial shape design. Therefore, we set design domain for cantilever space truss structure as an example model. And topology optimization is used to obtain optimum layout for them, and then size optimization method is used to find the optimum member size. Therefore, the reasonable initial optimal shapes of spatial truss structures can be obtained through the topology and size optimization using density method.

• Structural Engineering and Mechanics
• /
• v.76 no.6
• /
• pp.799-821
• /
• 2020

The optimum design of truss structures is one of the significant categories in structural optimization that has widely been applied by researchers. In the present study, new mathematical programming called Consistent Approximation (CONAP) method is utilized for the simultaneous optimization of the size and shape of truss structures. The CONAP algorithm has already been introduced to optimize some structures and functions. In the CONAP algorithm, some important parameters are designed by employing design sensitivities to enhance the capability of the method and its consistency in various optimum design problems, especially structural optimization. The cross-sectional area of the bar elements and the nodal coordinates of the truss are assumed to be the size and shape design variables, respectively. The displacement, allowable stress and the Euler buckling stress are taken as the design constraints for the problem. In the proposed method, the primary optimization problem is replaced with a sequence of explicit sub-problems. Each sub-problem is efficiently solved using the sequential quadratic programming (SQP) algorithm. Several truss structures are designed by employing the CONAP method to illustrate the efficiency of the algorithm for simultaneous shape and size optimization. The optimal solutions are compared with some of the mathematical programming algorithms, the approximation methods and metaheuristic algorithms those reported in the literature. Results demonstrate that the accuracy of the optimization is improved and the convergence rate speeds up.

• Journal of the Korean Society for Precision Engineering
• /
• v.28 no.4
• /
• pp.482-489
• /
• 2011

In practical design process, designer needs to find an optimal solution by using full factorial discrete combination, rather than by using optimization algorithm considering continuous design variables. So, ANOVA(Analysis of Variance) based on an orthogonal array, i.e. Taguchi method, has been widely used in most parts of industry area. However, the Taguchi method is limited for the shape optimization by using CAE, because the multi-level and multi-objective optimization can't be carried out simultaneously. In this study, a combined method was proposed taking into account of multi-level computational orthogonal array and TOPSIS(Technique for Order preference by Similarity to Ideal Solution), which is known as a classical method of multiple attribute decision making and enables to solve various decision making or selection problems in an aspect of multi-objective optimization. The proposed method was applied to a case study of the multi-level shape optimization of lower arm used to automobile parts, and the design space was explored via an efficient application of the related CAE tools. The multi-level shape optimization was performed sequentially by applying both of the neural network model generated from seven-level four-factor computational orthogonal array and the TOPSIS. The weight and maximum stress of the lower arm, as the objective functions for the multi-level shape optimization, showed an improvement of 0.07% and 17.89%, respectively. In addition, the number of CAE carried out for the shape optimization was only 55 times in comparison to full factorial method necessary to 2,401 times.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.2 no.2
• /
• pp.33-41
• /
• 1994

The procedure to design the engine mount is briefly discussed and the optimum shape design process of engine mounting rubber using a parametric approach is suggested. An optimization code is developed to determine the shape to meet the stiffness requirements of engine mounts, coupled with the commercial nonlinear finite element program ABAQUS. A bush type engine mount used in a current passenger car is chosen for an application model. The shape from the result of the parameter optimization is determined as a final model with some modifications. The shape and stiffness of each optimization stage are shown and the stiffness of the optimized model along the principal direction is compared with the design specification of the current model. Finally, an overview of the current status and future works for the engine mount design are discussed.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.10 no.2
• /
• pp.141-149
• /
• 2002

Most of mechanical failures are caused by repeated loadings and therefore they are strongly related to fatigue. To avoid the failures caused by fatigue, determination of an optimal shape of a structure is one of the very important factors in the initial design stage. Shape optimization for three types of specimens, which are very typical ones in opening mode in fracture mechanics, was accomplished by the linear elastic fracture mechanics and the growth-strain method in this study. The linear elastic fracture mechanics was used to estimate stress intensity factors and fatigue lives. And the growth-strain method was used to optimize the shape of the initial shape of the specimens. From the results of the shape optimization, it was concluded that shapes of three types of specimens optimized by the growth-strain method prolong their fatigue lives very much.

• Structural Engineering and Mechanics
• /
• v.53 no.4
• /
• pp.833-845
• /
• 2015

Natural frequencies of the structural systems should be far away from the excitation frequency in order to avoid or reduce the destructive effects of dynamic loads on structures. To accomplish this goal, a structural optimization on size and shape has been performed considering frequency constraints. Such an optimization problem has highly nonlinear property. Thus, the quality of the solution is not independent of the optimization technique to be applied. This study presents the performance evaluation of the recently proposed meta-heuristic algorithm called Teaching Learning Based Optimization (TLBO) as an optimization engine in the weight optimization of the truss structures under frequency constraints. Some examples regarding the optimization of trusses on shape and size with frequency constraints are solved. Also, the results obtained are tabulated for comparison. The results demonstrated that the performance of the TLBO is satisfactory. Additionally, TLBO is better than other methods in some cases.

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

• Proceedings of the KSME Conference
• /
• 2003.11a
• /
• pp.1328-1333
• /
• 2003

In the present study, an integrated framework of geometric modeling, analysis, and design optimization is proposed. Geometric modeling is based on B-spline surface representation. Geometrically-exact shell finite element is implemented in analysis module. Control points of the surface are selected as design variables for optimization, which can make the interaction easier between analysis and surface representation. Sequential linear programming(SLP) is adopted for the shape optimization of surfaces. For the computation of shape sensitivities, semi-analytical method is used. The developed integrated framework should serve as a powerful tool for the geometric modeling, analysis, and shape design of surfaces.