• Structural Engineering and Mechanics
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• v.76 no.5
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• pp.631-641
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• 2020

In the present work, an approach for the multiple time probabilistic characterization of the response of linear structural systems subjected to random non-Gaussian processes is presented. Its fundamental property is working directly on the multiple time probability density functions of the actions and of the response. This avoids of passing through the evaluation of the response statistical moments at multiple time or correlations, reducing the computational effort in a consistent measure. This approach is the extension to the multiple time case of a previously published dynamic Probability Transformation Method (PTM) working on a single evolution of the response statistics. The application to some simple examples has revealed the efficiency of the method, both in terms of computational effort and in terms of accuracy.

• Structural Engineering and Mechanics
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• v.75 no.6
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• pp.771-784
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• 2020

Reliability analysis techniques combining with various surrogate models have attracted increasing attention because of their accuracy and great efficiency. However, they primarily focus on the structures with continuous response, while very rare researches on the reliability analysis for structures with discontinuous response are carried out. Furthermore, existing adaptive reliability analysis methods based on importance sampling (IS) still have some intractable defects when dealing with small failure probability, and there is no related research on reliability analysis for structures involving discontinuous response and small failure probability. Therefore, this paper proposes a novel reliability analysis method called AGPC-IS for such structures, which combines adaptive Gaussian process classification (GPC) and adaptive-kernel-density-estimation-based IS. In AGPC-IS, an efficient adaptive strategy for design of experiments (DoE), taking into consideration the classification uncertainty, the sampling uniformity and the regional classification accuracy improvement, is developed with the purpose of improving the accuracy of Gaussian process classifier. The adaptive kernel density estimation is introduced for constructing the quasi-optimal density function of IS. In addition, a novel and more precise stopping criterion is also developed from the perspective of the stability of failure probability estimation. The efficiency, superiority and practicability of AGPC-IS are verified by three examples.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.692-697
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• 1994

In the actual sound environmental systems, it seems to be essentially difficult to exactly evaluate a whole probability distribution form of its response fluctuation, owing to various types of natural, social and human factors. Up to now, we very often reported two kinds of unified probability density expressions in the standard expansion from of Hermite and Laguerre type orthonormal series to generally evaluate non-Gaussian, non-linear correlation and/or non-stationary properties of the fluctuation phenomenon. However, in the real sound environment, there still remain many actual problems on the necessity of improving the above two standard type probability expressions for practical use. In this paper, first, a central point is focused on how to find a new probabilistic theory of practically evaluating the variety and complexity of the actual random fluctuations, especially through introducing some equivalence transformation toward two standard probability density expressions mentioned above in the expansion from of Hermite and Laguerre type orthonormal series. Then, the effectiveness of the proposed theory has been confirmed experimentally too by applying it to the actual problems on the response probability evaluation of various sound insulation systems in an acoustic room.

• 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 Earthquake Engineering Society of Korea
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• v.24 no.6
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• pp.243-251
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• 2020

In seismic design standards such as KDS 41 17 00 and ASCE 7, three procedures are provided to estimate seismic demands: equivalent lateral force (ELF), response spectrum analysis (RSA), and response history analysis (RHA). In this study, two steel special moment frames (SMFs) were designed with ELF and RSA, which have been commonly used in engineering practice. The collapse probabilities of the SMFs were evaluated according to FEMA P695 methodology. It was observed that collapse probabilities varied significantly in accordance with analysis procedures. SMFs designed with RSA (RSA-SMFs) had a higher probability of collapse than SMFs designed with ELF (ELF-SMFs). Furthermore, RSA-SMFs did not satisfy the target collapse probability specified in ASCE 7-16 whereas ELF-SMFs met the target probability.

• 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.

• School Mathematics
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• v.3 no.1
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• pp.101-108
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• 2001

Classroom exercise using the randomized response technique may be used to summarize a high school unit of instruction on probability. In this paper, we show that the derivation of the formula for this technique illustrates basic concepts in probability, such events being mutually disjoint and independent.

• Structural Engineering and Mechanics
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• v.47 no.1
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• pp.45-58
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• 2013

In structural reliability analysis, the response surface method is a powerful method to evaluate the probability of failure. However, the location of experimental points used to form a response surface function must be selected in a judicious way. It is necessary for the highly nonlinear limit state functions to consider the design point and the nonlinear trend of the limit state, because both of them influence the probability of failure. In this paper, in order to approximate the actual limit state more accurately, experimental points are selected close to the design point and the actual limit state, and consider the nonlinear trend of the limit state. Linear, quadratic and cubic polynomials without mixed terms are utilized to approximate the actual limit state. The direct Monte Carlo simulation on the approximated limit state is carried out to determine the probability of failure. Four examples are given to demonstrate the efficiency and the accuracy of the proposed method for both numerical and implicit limit states.

• Journal of the Korean Society of Safety
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• v.24 no.4
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• pp.53-58
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• 2009

The importance of process for repair and reinforcement of the bridge is increasing because of the lack of the fatigue load and stress, a lowering of the bridge load carrying capacity owing to impact and oscillation, deterioration on cultivation periods of the bridge, etc. Typically the experimenter values the bridge load carrying capacity by the real rating factor and response modification factor in bridge load rating through static load test and dynamic load test. But the error occurred in reliability of response modification factor in bridge load rating according to experience of experimenter. so tests of connecting probability theory and valuation of the bridge recently. The study is to compute the real load carrying capacity of the bridge and the rating factor and response modification factor on grade of the bridge, and calculate the probability of over-loaded truck load from Weigh In Motion(WIM) Data in FORTRAN programming applying to Monte-Carlo Simulation. At the result of this study, it is acquired that the new grade is computed for the probability of over-loaded truck load and surface inspection. The A grade is over 1.95, B grade is $1.55{\sim}1.94$, C grade is $1.26{\sim}1.54$, D grade is $1.14{\sim}1.25$, E grade is under 1.13 of rating factor, respectively.

• Wind and Structures
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• v.21 no.6
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• pp.609-623
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• 2015

Seismic reliability analysis of a jacket-type support structure for an offshore wind turbine was performed. When defining the limit state function by using the dynamic response of the support structure, a number of dynamic calculations must be performed in a First-Order Reliability Method (FORM). That means analysis costs become too high. In this paper, a new reliability analysis approach using a static response is used. The dynamic effect of the response is considered by introducing a new parameter called the Peak Response Factor (PRF). The probability distribution of PRF can be estimated by using the peak value in the dynamic response. The probability distribution of the PRF was obtained by analyzing dynamic responses during a set of ground motions. A numerical example is presented to compare the proposed approach with the conventional static response-based approach.