• Structural Engineering and Mechanics
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• v.54 no.3
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• pp.453-474
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• 2015

A hybrid approach of Particle Swarm Optimization (PSO) and Swallow Swarm Optimization algorithm (SSO) namely Hybrid Particle Swallow Swarm Optimization algorithm (HPSSO), is presented as a new variant of PSO algorithm for the highly nonlinear dynamic truss shape and size optimization with multiple natural frequency constraints. Experimentally validation of HPSSO on four benchmark trusses results in high performance in comparison to PSO variants and to those of different optimization techniques. The simulation results clearly show a good balance between global and local exploration abilities and consequently results in good optimum solution.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.11B no.2
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• pp.15-21
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• 2001

This paper presents an improved characteristic analysis methodology for a 5-phase hybrid stepping motor. The basic approach is based on the use of equivalent magnetic circuit taking into account the localized saturation throughout the hybrid stepping motor. The finite element method(FEM) is used to generate the magnetic circuit parameters for the complex stator and rotor teeth and airgap considering the saturation effects in tooth and poles. In addition, the neural network is used to map a change of parameters and predicts their approximation. Therefore, the proposed method efficiently improves the accuracy of analysis by using the parameter characterizing localized saturation effects and reduces the computational time by using the neural network. An improved circuit model of 5-phase hybrid stepping motor is presented and its application is provided to demonstrate the effectiveness of the proposed method.

• 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.

• Smart Structures and Systems
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• v.30 no.5
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• pp.463-477
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• 2022

In this paper, a hybrid vibration-impedance-based damage monitoring approach is experimentally evaluated for prestressed concrete (PSC) structures with local strand breakage. Firstly, the hybrid monitoring scheme is designed to alert damage occurrence from changes in vibration characteristics and to localize strand breakage from changes in impedance signatures. Secondly, a full-scale PSC anchorage is experimented to measure global vibration responses and local impedance responses under a sequence of simulated strand-breakage events. Finally, the measured data are analyzed using the hybrid monitoring framework. The change of structural condition (i.e., damage extent) induced by the local strand breakage is estimated by changes in a few natural frequencies obtained from a few accelerometers in the structure. The damaged strand is locally identified by tomography analysis of impedance features measured via an array of PZT (lead-zirconate-titanate) sensors mounted on the anchorage. Experimental results demonstrate that the strand breakage in the PSC structure can be accurately assessed by using the combined vibration and impedance features.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1105-1129
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• 2014

The unscented Kalman filter (UKF) has been developed for nonlinear model parametric identification, and it assumes that the model parameters are symmetrically distributed about their mean values without any constrains. However, the parameters in many applications are confined within certain ranges to make sense physically. In this paper, a constrained unscented Kalman filter (CUKF) algorithm is proposed to improve accuracy of numerical substructure modeling in hybrid testing. During hybrid testing, the numerical models of numerical substructures which are assumed identical to the physical substructures are updated online with the CUKF approach based on the measurement data from physical substructures. The CUKF method adopts sigma points (i.e., sample points) projecting strategy, with which the positions and weights of sigma points violating constraints are modified. The effectiveness of the proposed hybrid testing method is verified by pure numerical simulation and real-time as well as slower hybrid tests with nonlinear specimens. The results show that the new method has better accuracy compared to conventional hybrid testing with fixed numerical model and hybrid testing based on model updating with UKF.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.4
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• pp.436-443
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• 2015

In order to develop the PHEV(plug-in hybrid electric vehicle), the specific power transmission systems considering the PHEV system characteristics should be applied. A PHEV applied to series-parallel type hybrid power transmission system is a typical example. In this paper, the novel hybrid power systems are proposed by analyzing the existing PHEV system. The backward simulation program is developed to analyze the fuel efficiency of hybrid power system. Quasi-static models for each components such as engine, motor, battery and vehicle are included in the developed simulation program. To obtain an optimal condition for hybrid systems, an optimization approach called the dynamic programming is applied. The simulation is performed in various driving cycles. A weakness for the existing system is found through the simulation. To compensate for a discovered weakness, novel hybrid power systems are proposed by adding or moving the clutch to the existing system. Comparing the simulation results for each systems, the improved fuel efficiency for proposed systems are verified.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.115-127
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• 2020

In this paper, a sustainable close-loop supply chain (SCLSC) model is proposed for effectively managing the production, distribution and handling process of mobile phone. The proposed SCLSC model aims at maximizing total profit as economic factor, minimizing total CO₂ emission amount as environmental factor, and maximizing social influence as social factor in order to reinforce sustainability in it. Since these three factors are represented as each objective function in modeling, the proposed SCLSC model can be taken into consideration as a multi-objective optimization problem and solved using a hybrid genetic algorithm (HGA) approach. In numerical experiment, three different scales of the SCLSC model are presented and the efficiency of the HGA approach is proved using various measures of performance.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.3
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• pp.9-22
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• 2021

This study proposes a supply chain network (SCN) model considering supply disruption in assembly industry. For supply disruption, supplier disruption and its route disruption are simultaneously taken into consideration in the SCN model. With the simultaneous consideration, the SCN model can achieve its flexibility and efficiency. A mathematical formulation is suggested for representing the SCN model, and a proposed hybrid genetic algorithm (pro-HGA) is used for implementing the mathematical formulation. In numerical experiment, the performance of the pro-HGA approach is compared with those of some conventional approaches using the SCN models with various scales, and a sensitivity analysis considering the change of the numbers of suppliers and backup routes is done. Experimental results show that the performances of the pro-HGA approach are superior to those of the conventional approaches, and the flexibility and efficiency of the SCN model considering supply disruption are proved. Finally, the significance of this study is summarized and a potential future research direction is mentioned in conclusion.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.5
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• pp.391-401
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• 2009

The hybrid approach for structural experiments decomposes a structure into independent substructures that can be tested or simulated. The results from the decomposed substructures are combined to predict the behaviors of the entires structure. The hybrid approach is especially useful for the hybrid pseudo-dynamic tests that overcome the limitations of size of a test structure present in a shaking table test. The development of a computer system for the hybrid experiment requires a data model that formally organizes the information involved in the hybrid experiments. This paper provides the data model for representing the information involved in the hybrid experiments, by modifying the classes and attributes for the hybrid experiments in the Lehigh Model that is one of the data models for structural experiments. The data model for the hybrid experiments includes the classes for the physical substructures being tested and the analytical substructures being analyzed, and the simulation coordinator managing the overall experiments. Some objects for classes are implemented as an example to show the links among the classes. The data model presented in this paper can be applied for developing a computer system that helps structural engineers and researchers store, share, and access the information for the hybrid experiments.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.278-283
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• 1999