• Structural Engineering and Mechanics
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• v.18 no.1
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• pp.125-135
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• 2004

Industrial structure systems may have nonlinearity, and are also sometimes exposed to the danger of random excitation. This paper proposes a method to analyze response and reliability design of a complex nonlinear structure system under random excitation. The nonlinear structure system which is subjected to random process is modeled by finite element method. The nonlinear equations are expanded sequentially using the perturbation theory. Then, the perturbed equations are solved in probabilistic methods. Several statistical properties of random process that are of interest in random vibration applications are reviewed in accordance with the nonlinear stochastic problem.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.28-30
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• 2003

Probabilistic Load Flow(PLF) solution based on the method of moments is used for security assessment of bus voltages in power systems. Bus voltages, line currents, line admittances, generated real and reactive power, and bus loads are treated as complex random variables. These complex random variables are known in terms of probability density functions(PDF). Also, expressions for the convolutions of complex random variables in terms of moments and cumulants have been derived. Proposed PLF solution using the method of moments is fast, because the process of convolution of various complex random variables is performed in moment and cumulant domain. Therefore, the method is applied to security assessment of power systems in this paper. Finally, system operator also can be used information of security assessment to improve reliability of power systems.

• International Journal of Aerospace System Engineering
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• v.6 no.2
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• pp.1-10
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• 2019

In this paper, the probabilistic free vibration analysis of a geometrically coupled cantilever wing with uncertain material properties is carried out using stochastic finite element (SFEM) based on first order perturbation technique. Here, both stiffness and damping of the system are considered as random parameters. The bending and torsional rigidities are assumed as spatially varying second order Gaussian random fields and represented by Karhunen Loeve (K-L) expansion. Here, the expected value, standard deviation, and probability distribution of random natural frequencies and damping ratios are computed. The results obtained from the present approach are also compared with Monte Carlo simulations (MCS). The results show that the uncertain bending rigidity has more influence on the damping ratio and frequency of modes 1 and 3 while uncertain torsional rigidity has more influence on the damping ratio and frequency of modes 2 and 3.

• Earthquakes and Structures
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• v.27 no.4
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• pp.303-315
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• 2024

This study proposes a comprehensive methodology for estimating accumulative damage of bridge structures under multiple seismic excitations, in the framework of site-specific probabilistic hazard analysis. Specifically, a typical earthquake-prone region in China is chosen to perform probabilistic seismic hazard analysis (PSHA) to find the mean annual rate (MAR) of ground motion intensity at a specific level, based on which, a mass of ground motion observations is selected to construct random earthquake sequences with various number of shocks. Then, nonlinear time history analysis is implemented on the finite element (FE) model of a RC girder bridge at the site of interest, to investigate structural responses under different earthquake sequences, and to develop predictive model for cumulative damage computation, in which, a scalar seismic intensity measure (IM) is adopted and its performance in damage prediction is discussed by an experimental column. Furthermore, a mathematic model is established to calculate occurrence probability of earthquakes with various number of shocks, based on PSHA and homogenous Poisson random process, and a modified cumulative damage indicator is proposed, accounting for probabilistic occurrence of various earthquake scenarios. At end, the applicability of the proposed methodology to main shock and aftershock scenarios is validated, and characteristics of damage accumulation under different multiple earthquake scenarios are discussed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.2
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• pp.106-121
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• 2020

In order to make harbor outskirt facilities robust using the reliability-based design, probabilistic models of wave heights at varying stage of shoaling process optimized for Korean sea waves are prerequisite. In this rationale, we numerically simulate the nonlinear shoaling process of random waves over the beach with a sandbar at its foreshore. In doing so, comprehensive numerical models made of spatially filtered Navier-Stokes Eq., LES [Large Eddy Simulation], dynamic Smagorinsky turbulence closure were used. Considering the characteristics of swells observed at the east coast of Korean Peninsula, random waves were simulated using JONSWAP wave spectrum of various peak enhancement coefficients and random phase method. The coefficients of probabilistic models proposed in this study are estimated from the results of frequency analysis of wave crests and its associated trough detected by Wave by Wave Analysis of the time series of numerically simulated free surface displacements based on the threshold crossing method. Numerical results show that Modified Glukhovskiy wave height distribution, the most referred probabilistic models at finite water depth in the literature, over-predicts the occurring probability of relatively large and small wave heights, and under predicts the occurrence rate of waves of moderate heights. On the other hand, probabilistic models developed in this study show vary encouraging agreements. In addition, the discrepancy of the Modified Glukhovskiy distribution from the measured one are most visible over the surf zone, and as a result, the Modified Glukhovskiy distribution should be applied with caution for the reliability-based design of harbor outskirt facilities deployed near the surf-zone.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.09a
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• pp.243-250
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• 2001

Industrial machines are sometimes exposed to the danger of earthquake. In the design of a mechanical system, this factor should be accounted for from the viewpoint of reliability. A method to analyze a complex nonlinear structure system under random excitation is proposed. First, the actual random excitation, such as earthquake, is approximated to the corresponding Gaussian process far the statistical analysis. The modal equations of overall system are expanded sequentially. Then, the perturbed equations are synthesized into the overall system and solved in probabilistic way. Several statistical properties of a random process that are of interest in random vibration applications are reviewed in accordance with nonlinear stochastic problem. The obtained statistical properties of the nonlinear random vibration are evaluated in each substructure. Comparing with the results of the numerical simulation proved the efficiency of the proposed method.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.12
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• pp.70-79
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• 2020

This paper describes a comparative study of characteristics of probabilistic design using various reliability analysis methods in the structure design of an automatic salt collector. The thickness sizing variables of the main structural member were considered to be random variables, including the uncertainty of corrosion, which would be an inevitable hazard in the work environment of the automatic salt collector. Probabilistic performance functions were selected from the strength performances of the automatic salt collector structure. First-order reliability method, second-order reliability method, mean value reliability method, and adaptive importance sampling method were applied during the reliability analyses. The probabilistic design performances such as reliability probability and numerical costs based on the reliability analysis methods were compared to the Monte Carlo simulation results. The adaptive importance sampling method showed the most rational results for the probabilistic structure design of the automatic salt collector.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.232-237
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• 2001

The evaluation of specimen thickness effect of fatigue crack growth life by the simulation of probabilistic fatigue crack growth is presented. In this paper, the material resistance to fatigue crack growth is treated as a spatial stochastic process, which varies randomly on the crack surface. Using the previous experimental data, the non-Gaussian(eventually Weibull, in this report) random fields simulation method is applied. This method is useful to estimate the probability distribution of fatigue crack growth life and the variability due to specimen thickness by simulating material resistance to fatigue crack growth along a crack path.

• 전기의세계
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• v.22 no.2
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• pp.28-32
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• 1973

System modeling is applied in developing a probabilistic linear estimator for the load of an electric power system for the purpose of short term load forecasting. The model assumer that the load in given by the suns of a periodic discrete time serier with a period of 24 hour and a residual term such that the output of a discrete time dynamical linear system driven by a white random process and a deterministic input. And also we have established the main forecasting algorithms, which are essemtally the Kalman filter-predictor equations.

• Journal of Aerospace System Engineering
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• v.7 no.4
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• pp.1-11
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• 2013

In this study, probabilistic reliability analysis was conducted for hybrid rocket performance using Monte-Carlo Simulation. For the accuracy, reliability analysis was performed with experimental data. To simplify the analysis process, the oxidizer was supplied with constant pressure, so that pressure variation with time can be eliminated. And time-space averaged regression rate model was used. The regression rate is obtained with a series of experiments. For reliability analysis of thrust, constant exponent of regression rate is assumed that has probabilistic character. So, the efficiency of characteristic velocity has also probabilistic values. As a results, probability distribution of the thrust is obtained by Monte-Carlo simulation using random samples of the input parameter and validated under the 95% confidence level.