• Structural Monitoring and Maintenance
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• v.2 no.2
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• pp.133-143
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• 2015

Civil engineering infrastructure is aging and requires cost-effective maintenance strategies to enable infrastructure systems operate reliably and sustainably. This paper presents an approach for determining risk-cost balanced repair strategy of corrosion damaged reinforced concrete structures with consideration of uncertainty in structural resistance deterioration. On the basis of analytical models of cover concrete cracking evolution and bond strength degradation due to reinforcement corrosion, the effect of reinforcement corrosion on residual load carrying capacity of corroded reinforced concrete structures is investigated. A stochastic deterioration model based on gamma process is adopted to evaluate the probability of failure of structural bearing capacity over the lifetime. Optimal repair planning and maintenance strategies during the service life are determined by balancing the cost for maintenance and the risk of structural failure. The method proposed in this study is then demonstrated by numerical investigations for a concrete structure subjected to reinforcement corrosion. The obtained results show that the proposed method can provide a risk cost optimised repair schedule during the service life of corroded concrete structures.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.191-213
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• 2023

Unit distributions are frequently used in probability theory and statistics to depict meaningful variables having values between zero and one. Using convenient transformation, the unit inverse exponentiated weibull (UIEW) distribution, which is equally useful for modelling data on the unit interval, is proposed in this study. Quantile function, moments, incomplete moments, uncertainty measures, stochastic ordering, and stress-strength reliability are among the statistical properties provided for this distribution. To estimate the parameters associated to the recommended distribution, well-known estimation techniques including maximum likelihood, maximum product of spacings, least squares, weighted least squares, Cramer von Mises, Anderson-Darling, and Bayesian are utilised. Using simulated data, we compare how well the various estimators perform. According to the simulated outputs, the maximum product of spacing estimates has lower values of accuracy measures than alternative estimates in majority of situations. For two real datasets, the proposed model outperforms the beta, Kumaraswamy, unit Gompartz, unit Lomax and complementary unit weibull distributions based on various comparative indicators.

• Proceedings of the Korean Geotechical Society Conference
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• 1998.05a
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• pp.35-81
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• 1998

Distinct Element Method(DEM) has a great advantage to model the discontinuous behaviour of jointed rock masses such as rotation, sliding, and separation of rock blocks. Geometrical data of joints by a field monitoring is not enough to model the jointed rock mass though the results of DE analysis for the jointed rock mass is most sensitive to the distributional properties of joints. Also, it is important to use a properly joint law in evaluating the stability of a jointed rock mass because the joint is considered as the contact between blocks in DEM. In this study, a stochastic modelling technique is developed and the dilatant rock joint is numerically modelled in order to consider th geometrical and mechanical properties of joints in DE analysis. The stochastic modelling technique provides a assemblage of rock blocks by reproducing the joint distribution from insufficient joint data. Numerical Modelling of joint dilatancy in a edge-edge contact of DEM enable to consider not only mechanical properties but also various boundary conditions of joint. Preprocess Procedure for a stochastic DE model is composed of a statistical process of raw data of joints, a joint generation, and a block boundary generation. This stochastic DE model is used to analyze the effect of deviations of geometrical joint parameters on .the behaviour of jointed rock masses. This modelling method may be one tool for the consistency of DE analysis because it keeps the objectivity of the numerical model. In the joint constitutive law with a dilatancy, the normal and shear behaviour of a joint are fully coupled due to dilatation. It is easy to quantify the input Parameters used in the joint law from laboratory tests. The boundary effect on the behaviour of a joint is verified from shear tests under CNL and CNS using the numerical model of a single joint. The numerical model developed is applied to jointed rock masses to evaluate the effect of joint dilation on tunnel stability.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.420-422
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• 1998

In this paper, we propose a position-speed control of servo system with a state estimator. And also we utilized two mass modelling in order to deals with real system accurately. The overall control system consists of two parts: the position-speed controller and state estimator. The Kalman filter applied as state - feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear,unbiased and minimun error variance recursive algorithm to estimate the unknown state optimally. Therefore we consider the error problem about the servo system modelling, the measurement noise at low-speed ranges a stochastic system, and implement a optimal state observer. Performance of the proposed state estimator are demonstrated by computer simulations.

• Journal of Environmental Health Sciences
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• v.48 no.3
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• pp.131-137
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• 2022

Public interest has been increasing the focus on the management of exposure to pollutants and the related health effects. This study reviewed exposure assessment methodologies and addressed future directions. Exposure can be assessed by direct (exposure monitoring) or indirect approaches (exposure modelling). Exposure modelling is a cost-effective tool to assess exposure among individuals, but direct personal monitoring provides more accurate exposure data. There are several population exposure models: stochastic human exposure and dose simulation (SHEDS), air pollutants exposure (APEX), and air pollution exposure distributions within adult urban population in Europe (EXPOLIS). A South Korean population exposure model is needed since the resolution of ambient concentrations and time-activity patterns are country specific. Population exposure models could be useful to find the association between exposure to pollutants and adverse health effects in epidemiologic studies. With the advancement of sensor technology and the internet of things (IoT), exposure assessment could be applied in a real-time surveillance system. In the future, environmental health services will be useful to protect and promote human health from exposure to pollutants.

• Journal of the military operations research society of Korea
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• v.16 no.2
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• pp.29-42
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• 1990

This paper describes a Battle Group Combat Simulation Model (called 'BAGSIM'). BAGSIM is developed to be used as an experimental tool for studies about combat modelling at battle group level. Thus it takes many of the parameters and situations into consideration at this level, and it is designed to be easily adapted to represent equivalent situations to the other more aggregated models. Further the main processes occurring in its simulation procedure such as target detection process, target selection process, firing and killing processes are verified by comparison with the existing stochastic duel models.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.123-129
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• 2015

The Kalman filter has been widely used in the kinematic GPS positioning due to its flexibility and efficiency in computational points of view. At the same time, the relative positioning technique also provided the high precision positioning results by removing the systematic errors in the measurements significantly. However, the positioning quality may be degraded following to longer in baseline length. For this case, it is required that the remaining atmospheric effects, such as double-difference ionospheric delay and zenith wet delay, should be properly modeled by examining the characteristics of the stochastic processes. In general, atmospheric effects are estimated with the assumption of random walk, or the first-order Gauss-Markov stochastic process, which requires the precise modeling on the corresponding process noises. Therefore, we determined and provided the parameters for modelling the process noises for atmospheric effects. The auto-correlation functions are empirically determined at first, and then the parameters are extracted from the empirical auto-correlation function. In fact, the test results can be either applied directly, or used as guidance values for the modeling of process noises in the kinematic GPS positioning.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.27 no.4
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• pp.246-257
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• 2015

The progressive degradation paths of structures have quantitatively been tracked by using stochastic processes, such as Wiener process, gamma process and compound Poisson process, in order to consider both the sampling uncertainty due to the usual lack of damage data and the temporal uncertainty associated with the deterioration evolution. Several important features of stochastic processes which should carefully be considered in application of the stochastic processes to practical problems have been figured out through assessing cumulative damage and lifetime distribution as a function of time. Especially, the Wiener process and the gamma process have straightforwardly been applied to armors of rubble-mound breakwaters by the aid of a sample path method based on Melby's formula which can estimate cumulative damage levels of armors over time. The sample path method have been developed to calibrate the related-parameters required in the stochastic modelling of armors of rubble-mound breakwaters. From the analyses, it is found that cumulative damage levels of armors have surely been saturated with time. Also, the exponent of power law in time, that plays a significant role in predicting the cumulative damage levels over time, can easily be determined, which makes the stochastic models possible to track the cumulative damage levels of armors of rubble-mound breakwaters over time. Finally, failure probabilities with respect to various critical limits have been analyzed throughout its anticipated service life.

• Structural Engineering and Mechanics
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• v.68 no.4
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• pp.423-442
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• 2018

In this paper, masonry infilled reinforced concrete (RC) frames are analyzed through a probabilistic approach. A macro-modeling technique, based on an equivalent diagonal pin-jointed strut, has been resorted to for modelling the stiffening contribution of the masonry panels. Since it is quite difficult to decide which mechanical characteristics to assume for the diagonal struts in such simplified model, the strut width is here considered as a random variable, whose stochastic characterization stems from a wide set of empirical expressions proposed in the literature. The stochastic analysis of the masonry infilled RC frame is conducted via the Probabilistic Transformation Method by employing a set of space transformation laws of random vectors to determine the probability density function (PDF) of the system response in a direct manner. The knowledge of the PDF of a set of response indicators, including displacements, bending moments, shear forces, interstory drifts, opens an interesting discussion about the influence of the uncertainty of the masonry infills and the resulting implications in a design process.

• Bulletin of the Korean Mathematical Society
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• v.54 no.4
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• pp.1195-1219
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• 2017

In this paper, the limit behavior of solution for the $Schr{\ddot{o}}dinger$ equation with random dispersion and time-dependent nonlinear loss/gain: $idu+{\frac{1}{{\varepsilon}}}m({\frac{t}{{\varepsilon}^2}}){\partial}_{xx}udt+{\mid}u{\mid}^{2{\sigma}}udt+i{\varepsilon}a(t){\mid}u{\mid}^{2{\sigma}_0}udt=0$ is studied. Combining stochastic Strichartz-type estimates with $L^2$ norm estimates, we first derive the global existence for $L^2$ and $H^1$ solution of the stochastic $Schr{\ddot{o}}dinger$ equation with white noise dispersion and time-dependent loss/gain: $idu+{\Delta}u{\circ}d{\beta}+{\mid}u{\mid}^{2{\sigma}}udt+ia(t){\mid}u{\mid}^{2{\sigma}_0}udt=0$. Secondly, we prove rigorously the global diffusion-approximation limit of the solution for the former as ${\varepsilon}{\rightarrow}0$ in one-dimensional $L^2$ subcritical and critical cases.