• Journal of Korean Association for Spatial Structures
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• v.19 no.3
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• pp.51-59
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• 2019

A hybrid mid-story seismic isolation system with a smart damper has been proposed to mitigate seismic responses of tall buildings. Based on previous research, a hybrid mid-story seismic isolation system can provide effective control performance for reduction of seismic responses of tall buildings. Structural design of the hybrid mid-story seismic isolation system is generally performed after completion of structural design of a building structure. This design concept is called as an iterative design which is a general design process for structures and control devices. In the iterative design process, optimal design solution for the structure and control system is changed at each design stage. To solve this problem, the integrated optimal design method for the hybrid mid-story seismic isolation system and building structure was proposed in this study. An existing building with mid-story isolation system, i.e. Shiodome Sumitomo Building, was selected as an example structure for more realistic study. The hybrid mid-story isolation system in this study was composed of MR (magnetorheological) dampers. The stiffnessess and damping coefficients of the example building, maximum capacity of MR damper, and stiffness of isolation bearing were simultaneously optimized. Multi-objective genetic optimization method was employed for the simultaneous optimization of the example structure and the mid-story seismic isolation system. The optimization results show that the simultaneous optimization method can provide better control performance than the passive mid-story isolation system with reduction of structural materials.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.31-43
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• 2021

In this study, approximate design optimization using various meta-models was performed for the structural design of active type deck support frame. The active type deck support frame was newly developed to facilitate both transportation and installation of 20,000 ton class offshore plant topside. Structural analysis was carried out using the finite element method to evaluate the strength performance of the active type deck support frame in its initial design stage. In the structural analysis, the strength performances were evaluated for various design load conditions that were regulated in ship classification organization. The approximate optimum design problem based on meta-model was formulated such that thickness sizing variables of main structure members were determined by achieving the minimum weight of the active type deck support frame subject to the strength performance constraints. The meta-models used in the approximate design optimization were response surface method, Kriging model, and Chebyshev orthogonal polynomials. The results from approximate design optimization were compared to actual non-approximate design optimization. The Chebyshev orthogonal polynomials among the meta-models used in the approximate design optimization represented the most pertinent optimum design results for the structure design of the active type deck support frame.

• Journal of Auto-vehicle Safety Association
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• v.3 no.2
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• pp.5-10
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• 2011

Under the full frontal crash event, seatbelt system is the most typical and primary restraint device that prevents the second impact between an occupant and vehicle interior parts by limiting the forward motion of an occupant in the vehicle occupant packaging space. Today's restraint systems typically include the three-point seat belt with the pretensioner and the load limiter. A pretensioner preemptively tightens the seat belts removing any slack between a passenger and belt webbing which leads to early restraint of a passenger. After that a load limiter controls level of belt load by releasing the belt webbing to reduce occupant injurys. In this study, load characteristics of load limiters are optimized by the computer simulation with a MADYMO model for a frontal impact against the rigid wall at 56kph and then we suggest performance requirements. We derived optimum load characteristic from the results using four vehicle simulation models represented by the vehicle. Based on the results, we suggest the performance from the results of the second optimization using the simulation considering the design and the standardization. Finally, the performance requirements is verified by the sled tests including the load limiter device for the full vehicle condition.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.5
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• pp.62-67
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• 2010

Exhausting fossil fuel and increasing concern of air pollution have brought on the change of the focus of developing new vehicles from performance to fuel economy and emission. The gasoline engines adopting the naturally aspirated way use the throttle-body for engine load control. Therefore, its pumping loss increases more than that of the diesel engine, and also mostly operating in a partial load condition has bad influence on fuel economy and emission. In these days, the continuous variable valve timing system and variable induction system are adopted in order to improve fuel consumption and emission. In this study, we optimize the runner length and operate region of variable induction system to simulataneously improve the performance, fuel economy, and emission of gasoline engine with employing GT-Power as a CAE tool for engine analysis and PIAnO as PIDO tool for process integration and design optimization.

• Journal of Mechanical Science and Technology
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• v.18 no.4
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• pp.630-639
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• 2004

The Stewart platform manipulator is a closed-kinematics chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. However, this is a complex and nonlinear system, so the control performance of the system is not so good. In this paper, a new robust motion control algorithm is proposed. The algorithm uses partial state feedback for a class of nonlinear systems with modeling uncertainties and external disturbances. The major contribution is the design of a robust observer for the state and the perturbation of the Stewart platform, which is combined with a variable structure controller (VSC). The combination of controller and observer provides the robust routine called sliding mode control with sliding perturbation observe. (SMCSPO). The optimal gains of SMCSPO, which is determined by nominal eigenvalues, are easily obtained by genetic algorithm. The proposed fitness function that evaluates the gain optimization is to put sliding function. The control performance of the proposed algorithm is evaluated by the simulation and experiment to apply to the Stewart platform. The results showed high accuracy and good performance.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.1
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• pp.22-28
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• 2006

Establishment of practicalization technologies is becoming more important as dissemination of domestic PV system has been increased. To improve performance through PV system optimization, this paper presents loss factors analysis of PV system based on results of field operational test. Also, as simulation results are compared with actual operational ones, the main loss factors of PV system due to performance degradation are reviewed.

• JSTS:Journal of Semiconductor Technology and Science
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• v.3 no.1
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• pp.33-41
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• 2003

In this work, process optimization techniques for high frequency performance of HBTs are presented. The techniques are focused on reducing parasitic base resistance and base-collector capacitance, which are key elements determining the high frequency characteristics of HBTs. Several fabrication techniques, which can significantly reduce the parasitic elements of the HBTs for improved high frequency performance, are proposed and verified by the measured data of the fabricated devices.

• Smart Structures and Systems
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• v.19 no.4
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• pp.351-360
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• 2017

Protection of structures against natural hazards such as earthquakes has always been a major concern. Semi-active control combines the reliability of passive control and versatility and adaptability of active control. So it has recently become a preferred control method. This paper proposes an algorithm based on Uniform Deformation Theory to mitigate vulnerable buildings using magneto-rheological (MR) damper. Due to the successful performance of fuzzy logic in control of systems and its simplicity and intrinsically robustness, it is used here to regulate MR dampers. The particle swarm optimization (PSO) algorithm is also used as an adaptive method to develop a fuzzy control algorithm that is able to create uniform inter-story drifts. Results show that the proposed algorithm exhibited a desirable performance in reducing both linear and nonlinear seismic responses of structures. Performance of the presented method is indicated in compare with passive-on and passive-off control algorithms.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.201-219
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• 2014

This paper considers service deployment and priority optimization for multiple service-oriented applications sharing reusable services, which are deployed as multiple instances in the cloud. In order to handle variations in the workloads of the multiple applications, service instances of the individual reusable services are dynamically provisioned in the cloud. Also service priorities for each application in a particular reusable service are dynamically adjusted. In this paper, we propose an analytic performance model, based on a queueing network model, to predict the expected sojourn times of multiple service-oriented applications, given the number of service instances and priority disciplines in individual reusable services. We also propose a simple heuristic algorithm to search an optimal number of service instances in the cloud and service priority disciplines for each application in individual reusable services. A numerical example is also presented to demonstrate the applicability of the proposed performance model and algorithm to the proposed optimal decision problem.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.