• 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.63 no.6
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• pp.789-797
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• 2017

Recently, some integrated structural identification/damage detection and reliability evaluation of structures with uncertainties have been proposed. However, these techniques are applicable for off-line synthesis of structural identification and reliability evaluation. In this paper, based on the recursive formulation of the extended Kalman filter, an on-line integration of structural identification/damage detection and reliability evaluation of stochastic building structures is investigated. Structural limit state is expanded by the Taylor series in terms of uncertain variables to obtain the probability density function (PDF). Both structural component reliability with only one limit state function and system reliability with multi-limit state functions are studied. Then, it is extended to adopt the recent extended Kalman filter with unknown input (EKF-UI) proposed by the authors for on-line integration of structural identification/damage detection and structural reliability evaluation of stochastic building structures subject to unknown excitations. Numerical examples are used to demonstrate the proposed method. The evaluated results of structural component reliability and structural system reliability are compared with those by the Monte Carlo simulation to validate the performances of the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.486-495
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• 2009

This paper proposes a new methodology on reliability evaluation of a power system including solar cell generators (SCG). The SCGs using renewable energy resource such as solar radiation(SR) should be modeled as multi-state operational model because the uncertainty of the resource supply may occur an effect as same as the forced outage of generator in viewpoint of adequacy reliability of system. While a two-state model is well suited for modeling conventional generators, a multi-state model is needed to model the SCGs due to the random variation of solar radiation. This makes the method of calculating reliability evaluation indices of the SCG different from the conventional generator. After identifying the typical pattern of the SR probability distribution function(pdf) from SR actual data, this paper describes modelling, methodology and details process for reliability evaluation of the solar cell generators integrated with power system. Two test results indicate the viability of the proposed method.

• Advances in aircraft and spacecraft science
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• v.4 no.5
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• pp.585-611
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• 2017

This article covenants with the post buckling witticism of carbon nanotube reinforced composite (CNTRC) beam supported with an elastic foundation in thermal atmospheres with arbitrary assumed random system properties. The arbitrary assumed random system properties are be modeled as uncorrelated Gaussian random input variables. Unvaryingly distributed (UD) and functionally graded (FG) distributions of the carbon nanotube are deliberated. The material belongings of CNTRC beam are presumed to be graded in the beam depth way and appraised through a micromechanical exemplary. The basic equations of a CNTRC beam are imitative constructed on a higher order shear deformation beam (HSDT) theory with von-Karman type nonlinearity. The beam is supported by two parameters Pasternak elastic foundation with Winkler cubic nonlinearity. The thermal dominance is involved in the material properties of CNTRC beam is foreseen to be temperature dependent (TD). The first and second order perturbation method (SOPT) and Monte Carlo sampling (MCS) by way of CO nonlinear finite element method (FEM) through direct iterative way are offered to observe the mean, coefficient of variation (COV) and probability distribution function (PDF) of critical post buckling load. Archetypal outcomes are presented for the volume fraction of CNTRC, slenderness ratios, boundary conditions, underpinning parameters, amplitude ratios, temperature reliant and sovereign random material properties with arbitrary system properties. The present defined tactic is corroborated with the results available in the literature and by employing MCS.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.4
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• pp.44-50
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• 2010

Structural vibration is a significant problem in many multi-part or multi-component assemblies. In aircraft industry, structures are composed of various fasteners, such as bolts, snap, hinge, weld or other fastener or connector (collectively "fasteners"). Due to these, prediction and design involving dynamic characteristics is quite complicated. However, the current state of the art does not provide an analytical tool to effectively predict structure's dynamic characteristics, because consideration of structural uncertainties (i.e. material properties, geometric tolerance, dimensional tolerance, environment and so on) is difficult and very small fasteners in the structure cause a huge amount of analysis time to predict dynamic characteristics using the FEM (finite element method). In this study, to resolve the current state of the art, a new approach is proposed using the FEM and probabilistic analysis. Firstly, equivalent elements are developed using simple element (e.g. bar, beam, mass) to replace fasteners' finite element model. Developed equivalent elements enable to explain static behavior and dynamic behavior of the structure. Secondly, probabilistic analysis is applied to evaluate the PDF (probability density function) of dynamic characteristics due to tolerance, material properties and so on. MCS (Monte-Carlo simulation) is employed for this. Proposed methodology offers efficiency of dynamic analysis and reality of the field as well. Simple plates joined by fasteners are taken as an example to illustrate the proposed method.

• International Journal of Concrete Structures and Materials
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• v.19 no.1E
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• pp.11-16
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• 2007

Recently, probabilistic neural network (PNN) has been proposed to predict the compressive strength of concrete for the known effect of improvement on PNN by the iteration method. However, an empirical method has been incorporated in the PNN technique to specify its smoothing parameter, which causes significant uncertainty in predicting the compressive strength of concrete. In this study, a modified probabilistic neural network (MPNN) approach is hence proposed. The global probability density function (PDF) of variables is reflected by summing the heterogeneous local PDFs which are automatically determined by the individual standard deviation of each variable. The proposed MPNN is applied to predict the compressive strength of concrete using actual test data from a concrete company. The estimated results of MPNN are compared with those of the conventional PNN. MPNN showed better results than the conventional PNN in predicting the compressive strength of concrete and provided promising results for the probabilistic approach to predict the concrete strength by using the individual standard deviation of a variable.

• Structural Monitoring and Maintenance
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• v.4 no.1
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• pp.1-15
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• 2017

Installation of sensors networks for continuous in-service monitoring of structures and their efficiency conditions is a current research trend of paramount interest. On-line monitoring systems could be strategically useful for road infrastructures, which are expected to perform efficiently and be self-diagnostic, also in emergency scenarios. This work researches damage detection in composite concrete-steel structures that are typical for highway overpasses and bridges. The techniques herein proposed assume that typical damage in the deck occurs in form of delamination and cracking, and that it affects the peak power spectral density of dynamic curvature. The investigation is performed by combining results of measurements collected by long-gauge fiber optic strain sensors installed on monitored structure and a statistic approach. A finite element model has been also prepared and validated for deepening peculiar aspects of the investigation and the availability of the method. The proposed method for real time applications is able to detect a documented unusual behavior (e.g., damage or deterioration) through long-gauge fiber optic strain sensors measurements and a probabilistic study of the dynamic curvature power spectral density.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.13 no.4
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• pp.306-311
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• 2000

The purpose of this study is to research and develop solid polymer electrolyte(SPE) for Li polymer battery. The temperature dependence of conductivity impedance spectroscopy and electrochemical properties of PDF/PAN electrolytes as a function of a mixed ratio were reported for PVDF/PAN based polymer electrolyte films which were prepared by thermal gellification method of preweighed PVDF/PAN plasticizer and Li salt. The conductivity of PVDF/PAN electrolytes was 10$\^$-3/S/cm. 20PVDF5PEN LiCiO$\_$4//PC$\_$10//EC$\_$10/ electrolyte has the better conductivity compared to others. 20PVDF5PANLICIO$\_$4//PC$\_$10//EC$\_$10/ electroylte remains stable up to 5V vs. Li/Li$\^$+/. Steady state current method and ac impedance were used for the determination of transference numbers in PVDF/PAN electrolyte film. The transference number of 20PVDF5PANLiCO$\^$4//PC$\_$10//EC$\_$10/ electrolyte is 0.48.

• Nuclear Engineering and Technology
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• v.16 no.3
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• pp.136-140
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• 1984

A new medal is presented in order to evaluate the risk from a nuclear facility following accidents directly combining the on-site meteorological data using the Monte Carlo Method. To estimate the radiological detriment to the surrounding population-at-large (collective dose equivalent), in this study the probability distribution of each meteorological element based upon on-site data is analyzed to generate atmospheric dispersion conditions. The random sampling is used to select the dispersion conditions at any given time of effluent releases. In this study it is considered that the meteorological conditions such as wind direction, speed and stability are mutually independent and each condition satisfies the Markov condition. As a sample study, the risk of KNU-1 following the large LOCA was calculated, The calculated collective dose equivalent in the 50 mile region population from the large LOCA with 50 percent confidence level is 2.0$\times$10$^2$ man-sievert.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.645-656
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• 2020

In this study (Part II), the empirical formulation of corrosion model of a ship's ballast tank was developed to predict nonlinear time-dependent corrosion wastage based on the advanced data processing technique proposed by Part I. The detail on how to propose generalised mathematical formulation of corrosion model was precisely documented in the previous paper (Part I). The statistical scatter of corrosion data at any exposure time was investigated by the refined method and formulated based on a 2-parameter Weibull distribution which selected the best fit PDF. Throughout the nine (9) steps, empirical formulation of the ship's seawater ballast tank was successfully proposed and four (4) key step results were also obtained. The proposed method in Part I was verified and confirmed by this application of seawater ballast tank, thus making it possible to predict accurate behaviours of nonlinear timedependent corrosion. Developed procedures and obtained corrosion damage model for ship's seawater ballast tank can be used for development of engineering software.