• Earthquakes and Structures
• /
• v.3 no.6
• /
• pp.853-867
• /
• 2012

In this paper, a new type of passive energy dissipating system similar to added damping and stiffness (ADAS) and triangular added damping and stiffness (TADAS) is proposed and implemented in the analytical model of a building with hybrid structural system in the structure's base which we call it; Telescopic column. The behavior and performance of a high rise R.C. structure equipped with this system is investigated and compared with conventional base isolation systems such as rubber isolator bearings and friction pendulum bearings. For this purpose a series of ground acceleration records of the San Fernando, Long Beach and Imperial Valley earthquakes are used as the disturbing ground motions in a series of numerical simulations. The nonlinear numerical modeling which includes both material and geometric nonlinearities were carried out by using SAP2000 program. Results show suitable behavior of structures equipped with telescopic columns in controlling the upper stories drifts and accelerations.

• Journal of international Conference on Electrical Machines and Systems
• /
• v.2 no.1
• /
• pp.31-39
• /
• 2013

This paper presents small signal stability analysis of a doubly fed induction generator (DFIG) based wind farm including series dynamic braking resistor (SDBR) connected at the stator side. A detailed mathematical model of wind turbine, DFIG machine and converters and SDBR is presented in this paper to derive the complete dynamic equations of the studied system. Small signal stability of this system is carried out by modal and sensitivity analysis, participation factors and eigenvalue analysis. Finally, this paper presents an analysis of the dynamic behavior of DFIG based wind farm under voltage dip condition with and without SDBR.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2003.09a
• /
• pp.199-201
• /
• 2003

The monitoring effectiveness not only depends on the effectiveness of the network, but also the costs of the network. Generally the costs of the monitoring network are mainly on the equipment and personnel; the implementation and maintenance; the observation and sample connection; the sample analysis; and the data storage and processing. The cost of the monitoring network can be expressed as a function of monitoring frequency because the monitoring method can be an automatic or a manual measurement. To determine the sampling frequency of subsidiary groundwater monitoring stations, time series data of national groundwater monitoring stations were used. The proposed optimal sampling frequency for subsidiary groundwater monitoring station is about 7 to 20 days and the average frequency is about 2 weeks.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.864-865
• /
• 2008

This paper deals with d-q axis inductance measurements of IPMSM considering core loss at low speed. d-q axis inductance measurements generally are conducted at rated speed and parallel core loss model can be used to exclude core loss effects on inductances. Core loss is generally modeled parallel to input terminal of d-q axis equivalent circuit. Therefore, the effect of core loss on inductance calculation can be varied by core loss modeling. In this paper, d-q axis inductance is calculated parallel and series core loss modeling. Calculated inductances are compared to FEA results and it is concluded that series core loss modeling is more closed to FEA results at low speed.

• Proceedings of the KIEE Conference
• /
• 2008.10c
• /
• pp.177-179
• /
• 2008

This paper, we proposed the theoretical model which includes series resistance $R_s$ and shunt resistance $R_{sh}$ of single-crystalline PV module and used numerical method based on physics. Series resistance $R_s$ was derived from approach for p-n junction diode instead of established form obtained from the simulator with irradiance changes. Electrical output characteristics for PV modules to count the effect of $R_s$ were then studied. Finally simulation results were compared to experimental data leading to good agreement.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2011.05a
• /
• pp.473-473
• /
• 2011

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily reference evapotranspiration (ETo) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it consists of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily ETo data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as ETo modeling can be generalized using GMDH-NNM.

• Journal of Electrical Engineering and Technology
• /
• v.5 no.3
• /
• pp.415-422
• /
• 2010

The distributed flexible alternative current transmission system (D-FACTS) is a recently developed FACTS technology. Distributed Static Series Compensator (DSSC) is one example of DFACTS devices. DSSC functions in the same way as a Static Synchronous Series Compensator (SSSC), but is smaller in size, lower in price, and possesses more capabilities. Likewise, DSSC lies in transmission lines in a distributed manner. In this work, we designed a fuzzy logic controller to use the DSSC for enhancing transient stability in a two-machine, two-area power system. The parameters of the fuzzy logic controller are varied widely by a suitable choice of membership function and parameters in the rule base. Simulation results demonstrate the effectiveness of the fuzzy controller for transient stability enhancement by DSSC.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.15-15
• /
• 2000

In the past couple of years, there has been increasing interest in the fusion of neural networks and fuzzy logic. Most of the existing fused models have been proposed to implement different types of fuzzy reasoning mechanisms and inevitably they suffer from the dimensionality problem when dealing with complex real-world problem. To overcome the problem, we propose the self-organizing networks with activation nodes based on fuzzy inference and polynomial function. The proposed model consists of two parts, one is fuzzy nodes which each node is operated as a small fuzzy system with fuzzy implication rules, and its fuzzy system operates with Gaussian or triangular MF in Premise part and constant or regression polynomials in consequence part. the other is polynomial nodes which several types of high-order polynomials such as linear, quadratic, and cubic form are used and are connected as various kinds of multi-variable inputs. To demonstrate the effectiveness of the proposed method, time series data for gas furnace process has been applied.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2002.05a
• /
• pp.202-207
• /
• 2002

This paper deals with a novel shunted actuator, which has a capability to suppress multi-mode vibration amplitudes by using a pair of piezoceramic patches. In order to describe the characteristic behaviors of shunted dampers connected with a series and a parallel resistor-negative capacitive branch circuit, the stiffness ratio and loss factor with respect to the non-dimensional frequency are considered. To obtain a guideline model of a piezo/beam system connected with a series and a parallel resistor-negative capacitor branch circuit, the governing equations of motion is derived through Hamiltons principle and a piezo sensor equation as well as a shunt damping matrix is developed. The theoretical analysis shows that the shunted actuator developed in this study can significantly reduce multiple-mode vibration amplitudes simultaneously over the whole structural frequency range.

• Culinary science and hospitality research
• /
• v.5 no.1
• /
• pp.89-101
• /
• 1999

This study attempts to identify the most accurate quantitative forecasting technique for measuring the future level of demand for food ＆ beverage in super deluxe hotel in Seoul, which will subsequently lead to determining the optimal level of purchasing food ＆ beverage. This study, in detail, examines the food purchasing system of H hotel, reviews three rigorous univariate time series models and identify the most accurate forecasting technique. The monthly data ranging from January 1990 to December 1997 (96 observations) were used for the empirical analysis and the 1998 data were left for the comparison with the ex post forecast results. In order to measure the accuracy, MAPE, MAD and RMSE were used as criteria. In this study, Box-Jenkins model was turned out to be the most accurate technique for forecasting hotel food ＆ beverage demand among selected models generating 3.8％ forecast error in average.