• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.473-476
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• 2007

Location determination of mobile user via RSSI approach has received ample attention from researchers lately. However, it remains a challenging issue due to the complexities of RSSI signal propagation characteristics, which are easily exacerbated by the mobility of user. Hence, a segmentation-based linear spline interpolation method is proposed to cater for the dynamic fluctuation pattern of radio signal in complex environment. This optimization algorithm is proposed in addition to the current radiolocation's (CC2431, Chipcon, Norway) algorithm, which runs on IEEE802.15.4 standard. The enhancement algorithm involves four phases. First phase consists of calibration model in which RSSI values at different static locations are collected and processed to obtain the mean and standard deviation value for the predefined distance. RSSI smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the user is moving. Distances are computed using the segmentation formula obtain in the first phase. In situation where RSSI value falls in more than one segment, the ambiguity of distance is solved by probability approach. The distance probability distribution function(pdf) for each distances are computed and distance with the highest pdf at a particular RSSI is the estimated distance. Finally, with the distances obtained from each reference node, an iterative trilateration algorithm is used for position estimation. Experiment results obtained position the proposed algorithm as a viable alternative for location tracking.

• Structural Engineering and Mechanics
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• v.12 no.1
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• pp.1-16
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• 2001

A reliable and accurate method has been developed to predict the flexural deformation response of structural concrete members subject to service load. The method that has been developed relates the extent of concrete cracking, measured as a function of the magnitude of applied moment in a member, to the reduction in the effective moment of inertia of cracked reinforced concrete members under service load conditions. The ratio of the area of the moment diagram where the moment exceeds the cracking moment, to the total area of the moment diagram for any loading, provides the basis for the calculation of the effective moment of inertia. This ratio also represents mathematically a probability of crack occurrence. Verification of this method for the determination of the effective moment of inertia has been achieved from an experimental test program, and has included beam tests with different loading configurations, and shear wall tests subjected to a range of vertical and lateral load levels. Further verification of this method has been made with reference to the experimental investigation of other recently published work.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.5
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• pp.810-818
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• 1987

A new method is proposed to identify two-phase flow regimes in horizontal gas-liquid flow, based upon a statistical analysis of instantaneous pressure drop curves at an orifice. The probability density functions of the curves indicate distinct patterns depending upon the two-phase flow regime. The transition region also could be identified by the distribution shape of the probability density function. The statistical properties of the pressure drop are analyzed for various flow regimes and transitions. Finally, the data of flow patterns determined by the proposed method are compared with the flow pattern maps suggested by other investigators.

• Water for future
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• v.9 no.1
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• pp.101-105
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• 1976

This Study is developed in order to determine the probability of a raintall depth of short duration in Seoul as considering the profect life and the factor of safety of hydraulic structures. The raw annual maximum rainfall data are selected from 1915 to 1974 about short duration (10min-120min.) in Seoul. The selected data are treated by frequency analysis, and the hypothesis that the distribution fuction of the raw data is normal Distribution is performed by chi-square test that signifcance level has 5%. With the parameters (mean and standard deviation) of the accepted distribution function, the probabilitn of a rainfall depth can be easily determined on the graph which is made on this paper.

• Communications for Statistical Applications and Methods
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• v.18 no.3
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• pp.301-317
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• 2011

Statistical and probabilistic behaviors of fibers forming fiber webs of all kinds are of great significance in the determination of the uniformity and physical properties of the webs commonly found in many industrial products such as filters, membranes and non-woven fabrics. However, in studying the spatial geometry of the webs the observations must be theoretically as well as experimentally confined within a specified unit area. This paper provides a general theory and framework for computer simulation for quantifying the fiber segments bounded by the unit area in consideration of the "edge effects" resulting from the truncated length segments within the boundary. The probability density function and the first and second moments of the length segments found within the counting region were derived by properly defining the seeding region and counting region.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.95-102
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• 2003

To define an analytical model for a structural system or to assess damage in the system, system identification(SI) methods have been developed and widely applied. The paper presents a method of determining optimal sensor location(OSL) based on the maximum likelihood approach, which is applicable to modal SI methods. To estimate unknown parameters reliably, it is necessary that the information provided by the experiment should be maximized. By applying the Cramer-Rao inequality, a Fisher information matrix in terms of the probability density function of measurements is obtained from a lower bound of the estimation error. The paper also proposes a scheme of determining of OSL on damaged structures by using maximum strain energy factor. Simulation studies have carried out to investigate the proposed OSL algorithm for both undamaged and damaged structures.

• Journal of the military operations research society of Korea
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• v.18 no.1
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• pp.61-73
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• 1992

Up to the present, the operating time has been studied on only a single aircraft attacking a single target or multiple targets under enemy threats. This study is to determine optimal operating time and appropriate size of aircrafts attacking multiple targets. Measures of mission effectiveness is defined through derivation of the probability of the various events associated with operating. By using these measures, the expected benefit of operating and the expected cost of operating are generated as a function of time. To formulate operating time determination model, the expected gain of operating is defined as the difference between the expected benefit of operating and the expected cost of operating. The model can be used to determine optimal operating time which maximizes the expected gain of operating, and can be used as the basis for determining the appropriate size of aircrafts.

• Journal of Korea Water Resources Association
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• v.39 no.7 s.168
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• pp.575-581
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• 2006

This paper presents a systematic approach for the economical design of stormwater quality control systems. For the design of runoff quality control system (RQCS), the rainfall-runoff process requires the local rainfall data recorded continuously. In this study the rainfall probability distribution is assumed to follow an exponential decay function. Applying the exponential decay function, the normalized curves are derived to explain the non-exceedance probability distributions. The optimal curves for the determination of the RQCS size are derived based on the overflow risk. Comparison of the optimal capture volume and peak runoff rate to those computed by an urban rainfall-runoff model(ILLUDAS) demonstrates that the optimal CSOs(Combined Sewer Overflows) curves derived in this study can be utilized for the design of stormwater quality control systems in Korea avoiding an excessive computational effort based on over flow risks.

• Coupled systems mechanics
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• v.7 no.2
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• pp.197-209
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• 2018

Fiber-reinforced concrete (FRC) is a material with increasing application in civil engineering. Here it is assumed that the material consists of a great number of rather small fibers embedded into the concrete matrix. It would be advantageous to predict the mechanical properties of FRC using nondestructive testing; unfortunately, many testing methods for concrete are not applicable to FRC. In addition, design methods for FRC are either inaccurate or complicated. In three-point bending tests of FRC prisms, it has been observed that fiber reinforcement does not break but simply pulls out during specimen failure. Following that observation, this work is based on an assumption that the main components of a simple and rather accurate FRC model are mechanical properties of the concrete matrix and fiber pullout force. Properties of the concrete matrix could be determined from measurements on samples taken during concrete production, and fiber pullout force could be measured on samples with individual fibers embedded into concrete. However, there is no clear relationship between measurements on individual samples of concrete matrix with a single fiber and properties of the produced FRC. This work presents an inverse model for FRC that establishes a relation between parameters measured on individual material samples and properties of a structure made of the composite material. However, a deterministic relationship is clearly not possible since only a single beam specimen of 60 cm could easily contain over 100000 fibers. Our inverse model assumes that the probability density function of individual fiber properties is known, and that the global sample load-displacement curve is obtained from the experiment. Thus, each fiber is stochastically characterized and accordingly parameterized. A relationship between fiber parameters and global load-displacement response, the so-called forward model, is established. From the forward model, based on Levenberg-Marquardt procedure, the inverse model is formulated and successfully applied.