• Journal of Mechanical Science and Technology
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• v.20 no.10
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• pp.1662-1669
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• 2006

Since randomness and uncertainties of design parameters are inherent, the robust design has gained an ever increasing importance in mechanical engineering. The robustness is assessed by the measure of performance variability around mean value, which is called as standard deviation. Hence, constraints in robust optimization problem can be approached as probability constraints in reliability based optimization. Then, the FOSM (first order second moment) method or the AFOSM (advanced first order second moment) method can be used to calculate the mean values and the standard deviations of functions describing constraints and object. Among two methods, AFOSM method has some advantage over FOSM method in evaluation of probability. Nevertheless, it is difficult to obtain the mean value and the standard deviation of objective function using AFOSM method, because it requires that the mean value of function is always positive. This paper presented a special technique to overcome this weakness of AFOSM method. The mean value and the standard deviation of objective function by the proposed method are reliable as shown in examples compared with results by FOSM method.

• Journal of Mechanical Science and Technology
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• v.20 no.10
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• pp.1614-1625
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• 2006

This paper presents the kinematics and workspace optimization of the two different 2-DOF (Degrees-of-Freedom) planar parallel mechanisms: one (called 2-RPR mechanism) with translational actuators and the other (called 2-RRR mechanism) with rotational ones. First of all, the inverse kinematics and Jacobian matrix for each mechanism are derived analytically. Then, the workspace including the output-space and the joint-space is systematically analyzed in order to determine the geometric parameters and the operating range of the actuators. Finally, the kinematic optimization of the mechanisms is performed in consideration of their dexterity and rigidity. It is expected that the optimization results can be effectively used as a basic material for the applications of the presented mechanisms to more industrial fields.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.12 s.255
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• pp.1564-1572
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• 2006

This paper presents the kinematics and workspace optimization of the two different 2-DOF (Degrees-of-Freedom) planar parallel mechanisms: one (called 2-RPR mechanism) with translational actuators and the other (called 2-RRR mechanism) with rotational ones. First of all, the inverse kinematics and Jacobian matrix of each mechanism are derived analytically. Then, the workspace including the output-space and the joint-space is systematically analyzed in order to determine the geometric parameters and the operating range of the actuators. .Finally, the kinematic optimization of the mechanisms is performed with regards to their dexterity, stiffness and space utilization. It is expected that the optimization results can be effectively used as a basic material for the applications of the presented mechanisms to more industrial fields.

• Computers and Concrete
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• v.13 no.4
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• pp.457-482
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• 2014

This paper summarizes available literature on the optimization of reinforced concrete (RC) beams. The objective of optimization (e.g. minimum cost or weight), the design variables and the constraints considered by different studies vary widely and therefore, different optimization methods have been employed to provide the optimal design of RC beams, whether as isolated structural components or as part of a structural frame. The review of literature suggests that nonlinear deterministic approaches can be efficiently employed to provide optimal design of RC beams, given the small number of variables. This paper also presents spreadsheet implementation of cost optimization of RC beams in the familiar MS Excel environment to illustrate the efficiency of the exhaustive enumeration method for such small discrete search spaces and to promote its use by engineers and researchers. Furthermore, a sensitivity analysis is performed on the contribution of various design parameters to the variability of the overall cost of RC beams.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.401-408
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• 2006

An optimum design method for hybrid control systems is proposed in this study. By considering both active and passive control systems as a combined or a hybrid system, the optimization of the hybrid system can be achieved simultaneously. In the proposed approach, we consider design parameters of active control devices and the elements of the feedback gain matrix as design variables for the active control system. Required quantity of the added dampers are also treated as design variables for the passive control system. In the proposed method, the cost of both active and passive control devices, the required control efforts and dynamic responses of a target structure are selected as objective functions to be minimized. To effectively address the multi-objective optimization problem, we adopt a preference-based optimization model and apply a genetic algorithm as a numerical searching technique. As an example to verify the validity of the proposed optimization technique, a wind-excited 20-storey building with hybrid control systems is used and the results are presented.

• Structural Engineering and Mechanics
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• v.60 no.6
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• pp.1093-1117
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• 2016

Global sensitivity analysis (GSA) has been widely used to investigate the sensitivity of the model output with respect to its input parameters. In this paper a new single-solution search optimization algorithm is developed based on the GSA, and applied to the size optimization of truss structures. In this method the search space of the optimization is determined using the sensitivity indicator of variables. Unlike the common meta-heuristic algorithms, where all the variables are simultaneously changed in the optimization process, in this approach the sensitive variables of solution are iteratively changed more rapidly than the less sensitive ones in the search space. Comparisons of the present results with those of some previous population-based meta-heuristic algorithms demonstrate its capability, especially for decreasing the number of fitness functions evaluations, in solving the presented benchmark problems.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.116-126
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• 2019

In this paper, an improved one-against-one support vector machine algorithm is used to classify multiple power quality disturbances. To solve the problem of parameter selection, an improved particle swarm optimization algorithm is proposed to optimize the parameters of the support vector machine. By proposing a new inertia weight expression, the particle swarm optimization algorithm can effectively conduct a global search at the outset and effectively search locally later in a study, which improves the overall classification accuracy. The experimental results show that the improved particle swarm optimization method is more accurate than a grid search algorithm optimization and other improved particle swarm optimizations with regard to its classification of multiple power quality disturbances. Furthermore, the number of support vectors is reduced.

• Wind and Structures
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• v.34 no.3
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• pp.259-274
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• 2022

The present paper is focused on analyzing a set of Computational Fluid Dynamics (CFD) simulation data on reducing orthogonal peak base moment coefficients on a high-rise rectangular building with wings. The study adopts an aerodynamic optimization procedure (AOP) composed of CFD, artificial neural network (ANN), and genetic algorithm (G.A.). A parametric study is primarily accomplished by altering the wing positions with 3D transient CFD analysis using k - ε turbulence models. The CFD technique is validated by taking up a wind tunnel test. The required design parameters are obtained at each design point and used for training ANN. The trained ANN models are used as surrogates to conduct optimization studies using G.A. Two single-objective optimizations are performed to minimize the peak base moment coefficients in the individual directions. An additional multiobjective optimization is implemented with the motivation of diminishing the two orthogonal peak base moments concurrently. Pareto-optimal solutions specifying the preferred building shapes are offered.

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

• Proceedings of the KWS Conference
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• 1999.10a
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• pp.124-127
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• 1999