• Proceedings of the KSME Conference
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• 2004.04a
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• pp.234-239
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• 2004

A study on the probabilistic methodology for the estimation of the remaining life of Pressurized pipelines containing active corrosion defects is presented. This reliability assessment is earned out using extream value distribution of the corroded defects instead of already published failure perssure moded like NG18 or ASME B31G. The failure probability of pipelines depends on the number of corroded defects. and it could be calculated directly as the area exceeded a defined L V(Limited Value of corrosion depth). The remaining life of pressurized pipelines can also be estimated by the PDF of extream value distribution as calculating the exceeded area with a defined failure probability.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.6
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• pp.667-673
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• 2010

Recently, structures are becoming longer and higher because of the developments of new materials and construction techniques. However, such modern structures are more susceptible to excessive structural vibrations which cause deterioration in serviceability and structural safety. A modified probabilistic neural network(MPNN) approach is proposed to reduce the structural vibration. In this study, the global probability density function(PDF) of MPNN is reflected by summing the heterogeneous local PDFs automatically determined in the individual standard deviation of each variable. The proposed algorithm is applied for the vibration control of a three-story shear building model under Northridge earthquake. When the control results of the MPNN are compared with those of conventional PNN to verify the control performance, the MPNN controller proves to be more effective than PNN methods in decreasing the structural responses.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.690-693
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• 2005

In this paper, probabilistic distribution of fatigue life of chassis component is determined statistically by applying the design of experiments and the Pearson system. To construct $p-\varepsilon-N$ curve, the case that fatigue data are random variables is attempted. Probabilistic density function(p.d.f) for fatigue life is obtained by design of experiment and using this p.d.f fatigue reliability about any aimed fatigue life can be calculated. Lower control arm and rear torsion bar of chassis component are selected as examples for analysis. Component load histories, which are obtained by multi-body dynamic simulation for Belsian load history, are used. Finite element analysis are performed using commercial software MSC Nastran and fatigue analysis are performed using FE Fatigue. When strain-life curve itself is random variable, probability density function of fatigue life has very little difference from log-normal distribution. And the case of fatigue data are random variables, probability density functions are approximated to Beta distribution. Each p.d.f is verified by Monte-Carlo simulation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.3
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• pp.301-309
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• 2003

The non linear control algorithm with actuator saturation for a randomly excited oscillator has been widely explored and has shown promising results, but the probabilistic analysis of the algorithm has been rarely made due to its non-linear nature and the fact that the analytical solution of probability density function (PDF) for controlled responses does not exist. In this paper, a method for the probabilistic analysis on the non linear control algorithm with actuator saturation is proposed based on the equivalent non linear system method. Numerical examples are given to verify the approximation solution of PDF comparing to a statistically obtained PDF using a Gaussian white noise and a Kanai - Tagimi filtered Gaussian white noise.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.2 s.191
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• pp.110-117
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• 2007

In this paper, probabilistic distribution of chassis component fatigue life is determined statistically by applying the design of experiments and the Pearson system. To construct p - ${\varepsilon}$ - N curve, the case that fatigue data are random variables is attempted. Probabilistic density function (p.d.f) for fatigue life is obtained by the design of experiment and using this p.d.f fatigue reliability, any aimed fatigue life can be calculated. Lower control arm and rear torsion bar of chassis components are selected as examples for analysis. Component load histories which are obtained by multi-body dynamic simulation for Belsian load history are used. Finite element analysis is performed by using commercial software MSC Nastran and fatigue analysis is performed by using FE Fatigue. When strain-life curve itself is random variable, the probability density function of fatigue life has very little difference from log-normal distribution. And the cases of fatigue data are random variables, probability density functions are approximated to Beta distribution. Each p.d.f is verified by Monte-Carlo simulation.

• 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.

• Journal of Welding and Joining
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• v.23 no.6
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• pp.61-66
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• 2005

A probabilistic approach for evaluating failure risk is suggested in this paper. Probabilistic fracture analyses were performed for a pressurized pipe of a Cr-Mo steel reflecting variation of material properties at high temperature. A crack was assumed to be located along the weld fusion line. Probability density functions of major variables were determined by statistical analyses of material creep and creep crack growth data measured by the previous experimental studies by authors. Distributions of these variables were implemented in Monte Carlo simulation of this study. As a fracture parameter for characterizing growth of a fusion line crack between two materials with different creep properties, $C_t$ normalized with $C^*$ was employed. And the elapsed time was also normalized with tT, Resultingly, failure probability as a function of operating time was evaluated fur various cases. Conventional deterministic life assessment result was turned out to be conservative compared with that of probabilistic result. Sensitivity analysis for each input variable was conducted to understand the most influencing variable to the analysis results. Internal pressure, creep crack growth coefficient and creep coefficient were more sensitive to failure probability than other variables.

• Economic and Environmental Geology
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• v.33 no.4
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• pp.295-307
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• 2000

Probabilistic analysis is a powerful method to quantify variability and uncertainty common in engineering geology fields. In rock slope engineering, the uncertainty and variation may be in the form of scatter in orientations and geometries of discontinuities, and also test results. However, in the deterministic analysis, the factor of safety which is used to ensure stability of rock slopes, is based on the fixed representative values for each parameter without a consideration of the scattering in data. For comparison, in the probabilistic analysis, these discontinuity parameters are considered as random variables, and therefore, the reliability and probability theories are utilized to evaluate the possibility of slope failure. Therefore, in the probabilistic analysis, the factor of safety is considered as a random variable and replaced by the probability of failure to measure the level of slope stability. In this study, the stochastic properties of discontinuity parameters are evaluated and the stability of rock slope is analyzed based on the random properties of discontinuity parameters. Then, the results between the deterministic analysis and the probabilistic analysis are compared and the differences between the two analysis methods are explained.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.474-477
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• 1989

The PDA (Probabilistic Data Association) Filter proposes a new approach to the problem of tracking when the source of the measurement data is uncertain. The PDA filter shows good simulation results in a known clutter density. In this paper the PDA filter has been modified so that it can be applied when the clutter density is not known.