• Structural Engineering and Mechanics
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• v.49 no.1
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• pp.111-128
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• 2014

The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1815-1829
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• 2014

Recently frequent collapse of old fill dams has taken place, which increases social awareness in the safety of the infrastructure. Fill dams in Korea has been incautiously regarded as safe once the fill dam is considered to have a full capacity to retain a conservative design flood determined by government authorities. However, developed foreign countries has been managing their fill dams by introducing systematic risk assessment techniques over a long period of time. In this study, the system response probabilities of the deteriorated old fill dams in Korea were systematically evaluated and analyzed by using the internal erosion toolbox based on the event tree analysis technique. The probability of the existence of flaw and the magnitude of the hydraulic gradient through a potential crack can significantly influence the geotechnical system response probability. The results of this study show that the probability of the existence of flaw and the magnitude of the hydraulic gradient through a potential crack can significantly influence the geotechnical system response probability and the risk of the deteriorated fill dam can be quantitatively assessed.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1129-1139
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• 2006

Pearson's correlation coefficient and vector similarity are generally applied to The users' similarity weight of user based recommender system. This study is needed to find that the correlation coefficient of similarity weight is effected by the number of pair response and significance probability. From the classified correlation coefficient by the significance probability test on the correlation coefficient and pair of response, the change of MAE is studied by comparing the predicted precision of the two. The results are experimentally related with the change of MAE from the significant correlation coefficient and the number of pair response.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.686-691
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• 1994

For evaluating the response fluctuation of the actual environmental acoustic system excited by arbitrary random inputs, it is important to predict a whole probability distribution form closely connected with evaluation indexes Lx, Leq and so on. In this paper, a new type evaluation method is proposed by introducing three functional models matched to the prediction of the response probability distribution from a problem-oriented viewpoint. Because of the positive variable of the sound intensity, the response probability density function can be reasonably expressed theoretically by a statistical Laguerre expansion series form. The relationship between input and output is described by the regression relationship between the distribution parameters(containing expansion coefficients of this expression) and the stochastic input. These regression functions are expressed in terms of the orthogonal series expansion and their parameters are determined based on the least-squares error criterion and the measure of statistical independency.

• Journal of the Korean Society of Safety
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• v.31 no.4
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• pp.90-96
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• 2016

This study proposes a dynamic reliability analysis of control system as a method of quantitative evaluation of its performance in probabilistic terms. In this dynamic reliability analysis, the failure event is defined as an event that the dynamic response of the structural system exceeds a displacement limit, whereas the conventional reliability analysis method has limitations that do not properly assess the actual time history response of the structure subjected to dynamic loads, such as earthquakes and high winds, by taking the static response into account in the failure event. In this first paper, we discuss the control effect of the viscous damper on the seismic performance of the member-level failure where the failure event of the structural member consists of the union set of time-sequential member failures during the earthquake excitations and the failure probability of the earthquake-excited structural member is computed using system reliability approach to consider the statistical dependence of member failures between the subsequent time points. Numerical results demonstrate that the proposed approach can present a reliable assessment of the control performance of the viscous damper system in comparison with MCS method. The most important advantage of the proposed approach can provide us more accurate estimate of failure probability of the structural control system by using the actual time-history responses obtained by dynamic response analysis.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.275-282
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• 2006

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolernce of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or etimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte Carlo simulation and got the probabilistic sensitivity. The sensitivity of structural response with respect to in constant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• Structural Engineering and Mechanics
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• v.10 no.1
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• pp.17-26
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• 2000

This paper presents a case study with a multi-degree-of-freedom (MDOF) system where the Floor Response Spectra (FRS) have been derived from a large ensemble of ground motion accelerograms. The FRS are evaluated by the frequency response function which is calculated numerically. The advantage of this scheme over a repetitive time-history analysis of the entire structure for each accelerogram of the set has been highlighted. The present procedure permits generation of FRS with a specified probability of exceedence.

• Wind and Structures
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• v.10 no.1
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• pp.45-60
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• 2007

Transmission tower is a vital component in electrical system. In order to accurately compute the dynamic response and reliability of transmission tower under the excitation of wind loading, a new method termed as probability density evolution method (PDEM) is introduced in the paper. The PDEM had been proved to be of high accuracy and efficiency in most kinds of stochastic structural analysis. Consequently, it is very hopeful for the above needs to apply the PDEM in dynamic response of wind-excited transmission towers. Meanwhile, this paper explores the wind stochastic field from stochastic Fourier spectrum. Based on this new viewpoint, the basic random parameters of the wind stochastic field, the roughness length $z_0$ and the mean wind velocity at 10 m heigh $U_{10}$, as well as their probability density functions, are investigated. A latticed steel transmission tower subject to wind loading is studied in detail. It is shown that not only the statistic quantities of the dynamic response, but also the instantaneous PDF of the response and the time varying reliability can be worked out by the proposed method. The results demonstrate that the PDEM is feasible and efficient in the dynamic response and reliability analysis of wind-excited transmission towers.

• Structural Engineering and Mechanics
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• v.15 no.2
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• pp.239-248
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• 2003

The dynamic response analysis of closed loop control system based on probability for the intelligent truss structures with random parameters is presented. The expressions of numerical characteristics of structural dynamic response of closed loop control system are derived by means of the mode superposition method, in which the randomness of physical parameters of structural materials, geometric dimensions of active bars and passive bars, applied loads and control forces are considered simultaneously. The influences of the randomness of them on structural dynamic response are inspected by several engineering examples and some significant conclusions are obtained.

• Structural Engineering and Mechanics
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• v.57 no.1
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• pp.21-43
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• 2016

A conditional probability based approach known as Particle Filter Method (PFM) is a powerful tool for system parameter identification. In this paper, PFM has been applied to identify the vehicle parameters based on response statistics of the bridge. The flexibility of vehicle model has been considered in the formulation of bridge-vehicle interaction dynamics. The random unevenness of bridge has been idealized as non homogeneous random process in space. The simulated response has been contaminated with artificial noise to reflect the field condition. The performance of the identification system has been examined for various measurement location, vehicle velocity, bridge surface roughness factor, noise level and assumption of prior probability density. Identified vehicle parameters are found reasonably accurate and reconstructed interactive force time history with identified parameters closely matches with the simulated results. The study also reveals that crude assumption of prior probability density function does not end up with an incorrect estimate of parameters except requiring longer time for the iterative process to converge.