• Computers and Concrete
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• v.20 no.4
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• pp.469-481
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• 2017

This paper aims to analytically investigate the effect of shear stress at the concrete-steel interface on the mechanical behavior of the circular steel tube-confined concrete (STCC) stub columns with active and passive confinement subjected to axial compression. Nonlinear 3D finite element models divided into the four groups, i.e. circumferential-grooved, talc-coated, lubricated, and normal groups, with active and passive confinement were developed. An innovative method was used to simulate the actively-confined specimens, and then, the results of the finite element models were compared with those of the experiments previously conducted by the authors. It was revealed that both the predicted peak compressive strength and stress-strain curves have good agreement with the corresponding values measured for the confined columns. Then, the mechanical properties of the active and passive specimens such as the concrete-steel interaction, longitudinal and hoop stresses of the steel tube, confining pressure applied to the concrete core, and compressive stress-strain curves were analyzed. Furthermore, a parametric study was performed to explore the effects of the concrete compressive strength, steel tube diameter-to-wall thickness ratio, and prestressing level on the compressive behavior of the STCC columns. The results indicate that reducing or removing the interfacial shear stress in the active and passive specimens leads to an increase in the hoop stress and confining pressure, while the longitudinal stress along the steel tube height experiences a decrease. Moreover, prestressing via the presented method is capable of improving the compressive behavior of STCC columns.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.1
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• pp.103-110
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• 1998

The modeling of load characteristics is a difficult problem because of uncertainty of load. This research uses artificial neural networks which can approximate nonlinear problem to represent load characteristics. After the selection of typical load, active and reactive power for the variation of voltage and frequency is obtained from experiments. We constructed and learned ANN based on these data for component load identification. The learned ANN identified load characteristics for other voltage and/or frequency variation. In addition, the results of component load identification are presented to demonstrate the potentiality of the proposed method.method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.491-494
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• 2006

Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.

• Journal of KIISE:Information Networking
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• v.29 no.1
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• pp.48-56
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• 2002

This paper proposes an IP(Internet Protocol) multicast routing method by multiple tree routes. Multiple trees, instead of a single tree, improve the quality of multicast services with nonlinear link cost and huge traffic demand. The proposed method adds tree routes until it satisfies target conditions, and it splits the multicast traffic demand into the chosen tree routes. We develop a mathematical model and optimal conditions for traffic splitting. The method works on the problems with many different simultaneous multicast traffic. Various experiments were carried and the results show that the new multicasting is fairly effective on end-to-end quality of services.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1079-1082
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• 1996

To automate an excavator the control issues resulting from environmental uncertainties must be solved. In particular the interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition, operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a fuzzy logic controller(FLC) which controls the position of excavator's attachment. This approach enables the transfer of human heuristics and expert knowledge to the controller. Excavation experiments are carried out to check the performance of the FLC.

• Journal of Power Electronics
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• v.16 no.1
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• pp.238-248
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• 2016

The state-of-charge (SOC) and state-of-health (SOH) estimation of batteries play important roles in managing batteries for automotive applications. However, an accurate state estimation of a battery is difficult to achieve because of certain factors, such as measurement noise, highly nonlinear characteristics, strong hysteresis phenomenon, and diffusion effect of batteries. In certain vehicular applications, such as idle stop-start systems (ISSs), significant errors in SOC/SOH estimation may lead to a failure in restarting a combustion engine after the shut-off period of the engine when the vehicle is at rest, such as at a traffic light. In this paper, a dual extended Kalman filter algorithm with a dynamic equivalent circuit model of a lead-acid battery is proposed to deal with this problem. The proposed algorithm adopts a battery model by taking into account the hysteresis phenomenon, diffusion effect, and parameter variations for accurate state estimations of the battery. The validity of the proposed algorithm is verified through experiments by using an absorbed glass mat valve-regulated lead-acid battery and a battery sensor cable for commercial ISS vehicles.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.4
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• pp.317-325
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• 2011

In this paper a robust voltage controller for a single-phase UPS inverter is newly presented. The voltage controller is designed using ${\mu}$-based robust control scheme to simultaneously guarantee robust stability and robust tracking performance in the presence of load variations. Firstly the robust performance of the resulting controller is theoretically confirmed via ${\mu}$-analysis. Then simulations and experiments for the single-phase inverter system with linear and nonlinear loads demonstrate feasibility of the proposed control method providing improved performance - good regulation and fast dynamic response.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2130-2133
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• 2003

For real-time recognizing of the load vehicles a new Neural Network algorithm is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a Processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of vehicles, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through severa simulation experiments, real time reconstruction nonlinear image information is Processed. 1-D hardware has been composed and various experi with static and dynamic signals have implemented.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.7 no.1
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• pp.108-115
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• 1995

An efficient model for the dynamic analysis of caisson breakwaters under impulsive wave loadings is presented. The caisson structure is. regarded as a rigid body, and the rubble mound foundation is idealized as virtual added masses, springs, and dampers using the elastic half-space theory. The frequency-dependent hydrodynamic added mass and damping coefficients are considered by using the time memory functions and added mass at infinite frequency. To simulate the permanent sliding phenomenon of the caisson, the horizontal spring is modeled as a nonlinear spring with plastic behaviors. Comparisons with experimental results show that the present model gives fairly good results. Sensitivity analysis is performed for the relevant parameters affecting the dynamic responses of a caisson breakwater. Numerical experiments are also carried out to investigate the applicability to the prediction of permanent sliding distance and critical weight of the caisson.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.76-83
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• 2014

During PEMFC(Proton Exchange Membrane Fuel Cell) operation monitoring and diagnosis are important issues for reliability and durability. Stack defect can be followed by a critical cell voltage drop in the stack. One method for monitoring the cell voltage is CVM(Cell Voltage Monitoring), where all cells in the stack are electrically connected to a voltage measuring system and monitored these voltages. The other methods are based on the EIS(Electrochemical Impedance Spectroscopy) and on nonlinear frequency response. In this paper, intermodulation(IM) method for diagnosis PEMFC stack is introduced. To detect one or more critical PEMFC cell voltage PEMFC stack is excited by two or more test sinusoid current, and the frequency response of the stack voltage is analyzed. If one or more critical cell voltage exists, higher harmonics on the voltage frequency spectrum will appear. For the proposed IM method, stack simulation and experiments are conducted.