• Journal of the Korean Society of Safety
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• v.35 no.3
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• pp.49-57
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• 2020

In comparison with the existing static reliability analysis methods, the dynamic reliability analysis(DyRA) method is more suitable for estimating the failure probability of a structure subjected to earthquake excitations because it can take into account the frequency characteristics and damping capacity of the structure. However, the DyRA is known to have an issue of numerical stability due to the uncertainty in random sampling of the earthquake excitations. In order to solve this numerical stability issue in the DyRA approach, this study proposed two earthquake-scale factors. The first factor is defined as the ratio of the first earthquake excitation over the maximum value of the remaining excitations, and the second factor is defined as the condition number of the matrix consisting of the earthquake excitations. Then, we have performed parametric studies of two factors on numerical stability of the DyRA method. In illustrative example, it was clearly confirmed that the two factors can be used to verify the numerical stability of the proposed DyRA method. However, there exists a difference between the two factors. The first factor showed some overlapping region between the stable results and the unstable results so that it requires some additional reliability analysis to guarantee the stability of the DyRA method. On the contrary, the second factor clearly distinguished the stable and unstable results of the DyRA method without any overlapping region. Therefore, the second factor can be said to be better than the first factor as the criterion to determine whether or not the proposed DyRA method guarantees its numerical stability. In addition, the accuracy of the numerical analysis results of the proposed DyRA has been verified in comparison with those of the existing first-order reliability method(FORM), Monte Carlo simulation(MCS) method and subset simulation method(SSM). The comparative results confirmed that the proposed DyRA method can provide accurate and reliable estimation of the structural failure probability while maintaining the superior numerical efficiency over the existing methods.

• Journal of Environmental Science International
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• v.11 no.12
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• pp.1217-1226
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• 2002

This study aims at the effective estimation of water supply capacity of small scale reservoir and the proposal of the data which is necessary to establish the water resources management plan of down stream area of the reservoir in the future by comparison and examination about reservoir operation technique for the security of agricultural water in small scale reservoir. The result of flow calculation by Tank model is used for the input data as the inflow data which is needed for the analysis of water supply capacity. Stochastic method, simulation method, and optimization method are used to examine the water supply capacity, and water security amount is compared with each method. From the analyses of water supply capacities by each method, slightly different results are shown in spite of the effort to compare them equally using input data such as inflow data under equal conditions, and the comparison of water supply capacities by each method are as follows; linear planning method, simulation method, and transition probability matrix method in the order of amount from the largest. It is thought that the simulation method in which comparatively reasonable application of the inflow data is possible and is simulated in successive time series dam operation of the three methods used in this study thus, simulation model is proper to estimate the water supply capacity of agricultural small scale reservoir. And it is judged that the heightening of efficiency of water resources utilization according to the development of downstream area of dam may be possible using the upward readjusted water supply amount of $55.18{\tiems}10^6ton$ and $63.7{\times}10^6ton$ at 95% and 90% supply reliability respectively which are above the planning water supply amount of $50.0{\times}10^6$ton when the simulation method is introduced as the standard.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.179-190
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• 2010

This paper describes a new stochastic heuristic algorithm in engineering problem optimization especially in power system applications. An improved particle swarm optimization (PSO) called adaptive particle swarm optimization (APSO), mixed with simulated annealing (SA), is introduced and referred to as APSO-SA. This algorithm uses a novel PSO algorithm (APSO) to increase the convergence rate and incorporate the ability of SA to avoid being trapped in a local optimum. The APSO-SA algorithm efficiency is verified using some benchmark functions. This paper presents the application of APSO-SA to find the optimal location, type and size of flexible AC transmission system devices. Two types of FACTS devices, the thyristor controlled series capacitor (TCSC) and the static VAR compensator (SVC), are considered. The main objectives of the presented method are increasing the voltage stability index and over load factor, decreasing the cost of investment and total real power losses in the power system. In this regard, two cases are considered: single-type devices (same type of FACTS devices) and multi-type devices (combination of TCSC, SVC). Using the proposed method, the locations, type and sizes of FACTS devices are obtained to reach the optimal objective function. The APSO-SA is used to solve the above non.linear programming optimization problem for better accuracy and fast convergence and its results are compared with results of conventional PSO. The presented method expands the search space, improves performance and accelerates to the speed convergence, in comparison with the conventional PSO algorithm. The optimization results are compared with the standard PSO method. This comparison confirms the efficiency and validity of the proposed method. The proposed approach is examined and tested on IEEE 14 bus systems by MATLAB software. Numerical results demonstrate that the APSO-SA is fast and has a much lower computational cost.

• Structural Engineering and Mechanics
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• v.28 no.1
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• pp.89-105
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• 2008

The paper presents a study on the effects of soil-structure-interaction (SSI) on the performance of the compliant liquid column damper (CLCD) for the seismic vibration control of short period structures. The frequency-domain formulation for the input-output relation of a flexible-base structure with CLCD has been derived. The superstructure has been modeled as a linear, single degreeof-freedom (SDOF) system. The foundation has been considered to be attached to the underlying soil medium through linear springs and viscous dashpots, the properties of which have been represented by complex valued impedance functions. By using a standard equivalent linearization technique, the nonlinear orifice damping of the CLCD has been replaced by equivalent linear viscous damping. A numerical stochastic study has been carried out to study the functioning of the CLCD for varying degrees of SSI. Comparison of the damper performance when it is tuned to the fixed-base structural frequency and when tuned to the flexible-base structural frequency has been made. The effects of SSI on the optimal value of the orifice damping coefficient of the damper has also been studied. A more convenient approach for designing the damper while considering SSI, by using an established model of a replacement oscillator for the structure-soil system has also been presented. Finally, a simulation study, using a recorded accelerogram, has been carried out on the CLCD performance for the flexible-base structure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.11 no.1
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• pp.109-116
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• 1991

In recent years, hydrologists have been interested in the radial spectrum and its estimation in two dimensional storm field to construct simulation model of the rainfall. This paper deals with the problem of transformation from the spectrum or isotropic covariance function to two dimensional random field. The extended turning band method for the generation of random field is applied to the problem using the line generation method of one dimensional stochastic process by G.Matheron. Examples of this generation is chosen in the random components of the multidimensional rainfall model suggested by Bras and are given with a comparison between theoretical and sample statistics. In this numerical experiments it is observed that first and second order statistics can be conserved. Also the example of moving storm simulation through Bras model is presented with the appropriate parameters and sample size.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.365-370
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• 2000

A sliding mode fuzzy control (SMFC) algorithm is applied to design a controller for a benchmark problem on a wind- excited building. The structure is a 76-story concrete office tower with a height of 306 meters, hence the wind resistance characteristics are very important for the serviceability as well as the safety. A control system with an active tuned mass damper is assumed to be installed on the top floor. Since the structural acceleration is measured only at ,limited number of locations without measurement of the wind force, the structure of the conventional continuous sliding mode control may have the feed-back loop only. So, an adaptive least mean squares (LMS) filter is employed in the SMFC algorithm to generate a fictitious feed-forward loop. The adaptive LMS filter is designed based on the information of the stochastic characteristics of the wind velocity along the structure. A numerical study is carried out. and the performance of the present SMFC with the ,adaptive LMS filter is investigated in comparison with those of' other control, of algorithms such as linear quadratic Gaussian control, frequency domain optimal control, quadratic stability control, continuous sliding mode control, and H/sub ∞///sub μ/, control, which were reported by other researchers. The effectiveness of the adaptive LMS filter is also examined. The results indicate that the present algorithm is very efficient .

• Journal of The Korean Astronomical Society
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• v.30 no.1
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• pp.13-25
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• 1997

Sobolev approximation can be adopted to a macroscopic supersonic motion comparatively larger than a random (thermal) one. It has recently been applied not only to the winds of hot early type stars, but also to envelopes of late type giants and/or supergiants. However, since the ratio of wind velocity to stochastic one is comparatively small in the winds of these stars, the condition for applying the Sobolev approximation is not fulfilled any more. Therefore the validity of the Sobolev approximation must be checked. We have calculated exact P Cygni profiles with various velocity ratios, $V_\infty/V_{sto}$, using the accelerated lambda iteration method, comparing with those obtained by the Sobolev approximation. While the velocity ratio decrease, serious deviations have been occured over the whole line profile. When the gradual increase in the velocity structure happens near the surface of star, the amount of deviations become more serious even at the high velocity ratios. The investigations have been applied to observed UV line profile of CIV in the Copernicus spectrums $of\;\zeta\;Puppis\;and\;NV\;of\;\tau\;Sco$. In case of $\tau$ Sco which has an expanding envelope with the gradual velocity increase in the inner region, The Sobolev approximation has given the serious deviations in the line profiles.

• Korean Journal of Applied Biomechanics
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• v.17 no.2
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• pp.83-91
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• 2007

This experiment studied the change in a human's control of his or her static posture by analyzing the stabilogram diffusion and, by using the said study, evaluated the control ability of different groups with different experiences. The postures had a rising requirement of heel-rise according to three conditions: heel-toe, ball, toe; the groups were divided into dance major student and non-dance majors. The results of the critical points according to posture did not show a direct relation with the change in postures that had a rising requirement of heel-rise. The diffusion coefficient(D) had greater stochastic activity for short-term regions that utilize open-loop controls without feedback than for long-term regions that used closed-loop controls with feedback to maintain balance. The directional results of the body undergoing disturbance showed that A/P direction's diffusion coefficient (D) was larger than that of M/L direction. Both feet's planar diffusion coefficients were a linear combination of the diffusion coefficients calculated for the x and y axis. In studying the different abilities to control posture between a dance major student and a non-dance majors, a comparison of open-loop control's diffusion coefficient(D) was effective, and dance major student had superior control ability to that of non-dance majors.

• Journal of the Korean Society of Safety
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• v.21 no.4 s.76
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• pp.25-32
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• 2006

LonWorks over IP(LonWorks-IP) virtual device network(VDN) is an integrated form of LonWorks device network and IP data network. In especially real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. The time delay in servo control on LonWorks-IP based VDN has highly stochastic nature. LonWorks-IP based VDN induced transmission delay deteriorates the performance and stability of the real-time distributed control system and can't give an effective preventive and predictive maintenance. In order to guarantee the stability and performance of the system, and give an effective preventive and predictive maintenance, LonWorks-IP based VDN induced time-varying uncertain time delay needs to be predicted and compensated. In this paper new Pill control scheme based on Smith predictor, disturbance observer and band pass filter is proposed and tested through computer simulation about position control of DC servo motor. It is shown that how can the proposed control scheme be designed to minimize the effects of uncertain varying time delay and model uncertainties. The validity of the proposed control scheme is compared and demonstrated with the comparison of internal model controllers(IMC) based on Smith predictor with and without disturbance observer.

• Advances in environmental research
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• v.4 no.2
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• pp.83-104
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• 2015

Air Quality Index (AQI) is a pointer to broadcast short term air quality. This paper presents one day ahead AQI forecasting on seasonal basis for three major cities in Maharashtra State, India by using Artificial Neural Networks (ANN) and Genetic Programming (GP). The meteorological observations & previous AQI from 2005-2008 are used to predict next day's AQI. It was observed that GP captures the phenomenon better than ANN and could also follow the peak values better than ANN. The overall performance of GP seems better as compared to ANN. Stochastic nature of the input parameters and the possibility of auto-correlation might have introduced time lag and subsequent errors in predictions. Spectral Analysis (SA) was used for characterization of the error introduced. Correlational dependency (serial dependency) was calculated for all 24 models prepared on seasonal basis. Particular lags (k) in all the models were removed by differencing the series, that is converting each i'th element of the series into its difference from the (i-k)"th element. New time series is generated for all seasonal models in synchronization with the original time line & evaluated using ANN and GP. The statistical analysis and comparison of GP and ANN models has been done. We have proposed a promising approach of use of GP coupled with SA for real time prediction of seasonal multicity AQI.