• International Journal of Automotive Technology
• /
• v.8 no.3
• /
• pp.337-342
• /
• 2007

A multi-objective optimization technique was implemented to obtain optimal topologies of the inner reinforcement for a vehicle's hood simultaneously considering the static stiffness of bending and torsion and natural frequency. In addition, a smoothing scheme was used to suppress the checkerboard patterns in the ESO method. Two models with different curvature were chosen in order to investigate the effect of curvature on the static stiffness and natural frequency of the inner reinforcement. A scale factor was employed to properly reflect the effect of each objective function. From several combinations of weighting factors, a Pareto-optimal topology solution was obtained. As the weighting factor for the elastic strain efficiency went from 1 to 0, the optimal topologies transmitted from the optimal topology of a static stiffness problem to that of a natural frequency problem. It was also found that the higher curvature model had a larger static stiffness and natural frequency than the lower curvature model. From the results, it is concluded that the ESO method with a smoothing scheme was effectively applied to topology optimization of the inner reinforcement of a vehicle's hood.

• Computational Structural Engineering
• /
• v.7 no.1
• /
• pp.117-124
• /
• 1994

Multi-level Multi-objective optimization(MLMO) for reinforced concrete framed structure is performed, and compared with the results of single-level single-objective optimization. MLMO method allows flexibility to meet the design needs such as deflection and cost of structures using weighting factors. Using Multi-level formulation, the numbers of constraints and variables are reduced at each levels, and the optimization formulation becomes simplified. The force approximation method is used to reflect the variation in design variables between the substructures, and thus coupling is maintained. And the linear approximated constraints and objective function are used to reduce the number of structural analysis in optimization process. It is shown that the developed algorithm with move limit can converge effectively to optimal solution.

• Journal of Korean Society of Steel Construction
• /
• v.9 no.3 s.32
• /
• pp.457-465
• /
• 1997

The Shape optimization makes it possible to reduce the weight of structure and cost then member sizing optimization. A vast amount of imprecise information is existed in constraints of the optimum design. It is very difficult and sometimes confusing to describe and to deal with the several criteria which contain fuzzy degrees of relatives importance. This paper proposed weighting strategies in the multiobjective shape optimization of fuzzy structural system by ${\alpha}$-cut approach. The algorithm in this research is numerically tested for 2-bar truss structure. The result show that. the user can choose the one optimum solution in practices as obtaining the optimum solutions according to the ${\alpha}$-cut approach, weight of volume and displacement.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.28 no.7
• /
• pp.879-886
• /
• 2004

A numerical optimization has been carried out to determine the shape of the three-dimensional channel with oblique ribs attached on both walls to enhance turbulent heat transfer. The response surface based optimization is used as an optimization technique with Reynolds-averaged Navier-Stokes analysis of fluid flow and heat transfer. Shear stress transport (SST) turbulence model is used as a turbulence closure. Numerical results fur heat transfer rate show good agreements with experimental data. four dimensionless variables such as, rib pitch-to-rib height ratio, rib height-to-channel height ratio, streamwise rib distance on opposite wall to rib pitch ratio, and the attack angle of the rib are chosen as design variables. The objective function is defined as a linear combination of heat-transfer and friction-loss related coefficients with a weighting factor. D-optimal method is used to determine the training points as a means of design of experiment. Sensitivity of the objective parameters to each design variable has been analyzed. And, optimal values of the design variables have been obtained in a range of the weighting factor.

• The Journal of the Acoustical Society of Korea
• /
• v.18 no.4
• /
• pp.23-30
• /
• 1999

In this study, we propose a new optimization algorithm for a withdrawal weighted SAW transversal filter to satisfy given, specifications such as bandwidth, ripple, insertion loss, and sidelobe rejection level. An analysis tool for the withdrawal weighted filter has been produced by means of the delta function model, and has been applied to the design of a filter consisting of an uniform input IDT and a withdrawal weighted output IDT. This optimization algorithm consists of three routines, which eventually determines eight design parameters to satisfy the performance specifications. At the first step, the number of input and output IDT fingers and their geometrical size are determined by the insertion loss specification. At the next step, the bandwidth is controlled by the change of the IDT finger position. Finally, the sidelobe rejection level is modified through the add/skip technique of IDT fingers. The algorithm in this paper is distinct from conventional techniques in that it can simultaneously consider all the specifications such as bandwidth, ripple, sidelobe rejection level and insertion loss, and optimize the geometry of the withdrawal weighted SAW filter.

• Structural Engineering and Mechanics
• /
• v.65 no.2
• /
• pp.173-181
• /
• 2018

In this paper, finite element (FE) model updating based on multi-objective optimization with the surrogate model for a steel plate girder bridge is investigated. Conventionally, FE model updating for bridge structures uses single-objective optimization with finite element analysis (FEA). In the case of the conventional method, computational burden occurs considerably because a lot of iteration are performed during the updating process. This issue can be addressed by replacing FEA with the surrogate model. The other problem is that the updating result from single-objective optimization depends on the condition of the weighting factors. Previous studies have used the trial-and-error strategy, genetic algorithm, or user's preference to obtain the most preferred model; but it needs considerable computation cost. In this study, the FE model updating method consisting of the surrogate model and multi-objective optimization, which can construct the Pareto-optimal front through a single run without considering the weighting factors, is proposed to overcome the limitations of the single-objective optimization. To verify the proposed method, the results of the proposed method are compared with those of the single-objective optimization. The comparison shows that the updated model from the multi-objective optimization is superior to the result of single-objective optimization in calculation time as well as the relative errors between the updated model and measurement.

• Nuclear Engineering and Technology
• /
• v.29 no.1
• /
• pp.68-77
• /
• 1997

The reactor power control system is described in the fashion of the order increased LQR system. To obtain the optimal state feedback gain vectors, the weighting matrix of the performance function should be determined. Since the contentional method has some limitations, stochastic searching methods are investigated to optimize the LQR weighting matrix using the modified genetic algorithm combined with the simulated annealing, a new optimizing tool named the hybrid MGA-SA is developed to determine the weighting parameters of the LQR system. This optimizing tool provides a more systematic approach in designing the LQR system. Since it can be easily incorporated with any forms of the cost function, it also provides the great flexibility in the optimization problems.

• The KSFM Journal of Fluid Machinery
• /
• v.10 no.2 s.41
• /
• pp.7-15
• /
• 2007

A numerical procedure for optimizing the shape of three-dimensional channel with V-shaped ribs extruded on both walls has been carried out to enhance the turbulent heat transfer. The response surface based optimization is used as an optimization technique with Reynolds-averaged Wavier-stoked analysis. Shear stress transport (SST) turbulence model is used as a turbulence closure. Computational results for average heat transfer rate show good agreements with experimental data. The objective function is defined as a linear combination of heat transfer and friction loss-related terms with a weighting factor. Three dimensionless variables such as, rib pitch-to-rib height ratio, rib height-to-channel height ratio, and the attack angle of the rib are chosen as design variables. Nineteen training points obtained by D-optimal designs for three design variables construct a reliable response surface. In the sensitivity analysis, it is found that the objective function is most sensitive to the ratio of rib height-to-channel height ratio. And, optimal values of design variables have been obtained in a range of the weighting factor.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.28 no.9
• /
• pp.1051-1057
• /
• 2004

A numerical optimization procedure for the shape of three-dimensional channel with angled ribs mounted on one of the walls to enhance turbulent heat transfer is presented. The response surface method is used as an optimization technique with Reynolds-averaged Wavier-Stokes analyses of flow and heat transfer. SST turbulence model is used as a turbulence closure. Computational results for local heat transfer rate show reasonable agreements with experimental data. The pitch-to-height ratio of the rib and rib height-to-channel height ratio are set to be 9.0 and 0.1, respectively, and width-to-rib height ratio and attack angle of the rib are chosen as design variables. The objective function is defined as a linear combination of heat-transfer and friction-loss related terms with weighting factor. Full-factorial experimental design method is used to determine the data points. Optimum shapes of the channel have been obtained in the range from 0.0 to 0.1 of weighting factor.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.6
• /
• pp.789-799
• /
• 1999

In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.