• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.55-69
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• 2009

A quasi ideal importance sampling simulation method combined in the conditional expectation is proposed for the structural reliability estimation. The quasi ideal importance sampling joint probability density function (p.d.f.) is so composed on the basis of the ideal importance sampling concept as to be proportional to the conditional failure probability multiplied by the p.d.f. of the sampling variables. The respective marginal p.d.f.s of the ideal importance sampling joint p.d.f. are determined numerically by the simulations and partly by the piecewise integrations. The quasi ideal importance sampling simulations combined in the conditional expectation are executed to estimate the failure probabilities of structures with multiple failure surfaces and it is shown that the proposed method gives accurate estimations efficiently.

• Wind and Structures
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• v.18 no.6
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• pp.651-668
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• 2014

Wind tunnel tests are conducted to investigate the wind loads on vertical fixed-roof cylindrical tanks with a very low aspect ratio of 0.275, which is a typical ratio for practical tanks with a volume of $100,000m^3$. Both the flat-roof tank and the dome-roof tank are investigated in present study. The first four moments of the measured wind pressure, including the mean and normalized deviation pressure, kurtosis and skewness of the pressure signal, are obtained to study the feature of the wind loads. It is shown that the wind loads are closely related to the behavior of flow around the structure. For either tank, the mean wind pressures on the cylinder are positive on the windward area and negative on the sides and the wake area, and the mean wind pressures on the whole roof are negative. The roof configurations have no considerable influence on the mean pressure distributions of cylindrical wall in general. Highly non-Gaussian feature is found in either tank. Conditional sampling technique, envelope method, and the proper orthogonal decomposition (POD) analysis are employed to investigate the characteristics of wind loads on the cylinder in more detail. It is shown that the patterns of wind pressure obtained from conditional sampling are similar to the mean pressure patterns.An instantaneous pressure coefficient can present a wide range from the maximum value to the minimum value. The quasi-steady assumption is not valid for structures considered in this paper according to the POD analysis.

• ETRI Journal
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• v.14 no.4
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• pp.19-27
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• 1992

Since. as is well known, direct computation of the reliability for a large-scaled and complex net work generally requires exponential time, a variety of alternative methods to estimate the network reliability using simulation have been proposed. Monte Carlo sampling is the major approach to estimate the network reliability using simulation. In the paper, a dynamic Monte Carlo sampling method, called conditional minimal cut set (CMCS) algorithm, is suggested. The CMCS algorithm simulates a minimal cut set composed of arcs originated from the (conditional) source node until s-t connectedness is confirmed, then reduces the network on the basis of the states of simulated arcs. We develop the importance sampling estimator and the total hazard estimator and compare the performance of these simulation estimators. It is found that the CMCS algorithm is useful in reducing variance of network reliability estimator.

• Wind and Structures
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• v.8 no.1
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• pp.13-34
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• 2005

This paper presents an analysis of wind velocity and pressure data obtained in a rural environment with a view to identifying the vortex structures present within the flow and examining the relationship between pressure and dynamic pressure. The data is analysed using both conventional analysis and conditional sampling. A method examining the eigenvalues of a matrix formed by the addition of the square of the strain tensor and the square of the vorticity tensor is also investigated. This method illustrates that there are a number of vortex structures present in the flow. The work presented in this paper suggests that the extreme events occur as a result of the superposition of two independent mechanisms.

• Journal of Korean Society for Quality Management
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• v.26 no.1
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• pp.88-98
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• 1998

Process capability indices are used to determine whether a production process is capable of producing items within a specified tolerance. Using conditional distribution, we study some process capability indices ${\hat{C}}_{Gp}$, ${\hat{C}}_{Gpk}$, ${\hat{C}}_{Gpm}$ under conjugate prior distribution. We consider some process capability indices with Gibbs sampling method. Also, we examine some small sample properties related to these estimaters by some simulations.

• Economic and Environmental Geology
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• v.30 no.5
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• pp.493-498
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• 1997

The purpose of this study is to develop geostatistical model for evaluating the abundance of deep-sea manganese nodule. The abundance data used in this study were obtained from the KODOS (Korea Deep Ocean Study) area. The variation of nodule abundance was very high within short distance, while sampling methods was very limited. As the distribution of nodule abundance showed non-gaussian, indicator simulation method was used instead of conditional simulation method and/or ordinary kriging. The abundance data were encoded into a series of indicators with 6 cutoff values. They were used to estimate the conditional probability distribution function (cpdf) of the nodule abundance at any unsampled location. The standardized indicator variogram models were obtained according to variogram analysis. This SIS method had the advantage over other traditional techniques such as the turning bands method and ordinary kriging. The estimating values by indicator conditional simulation near high abundance area were more detailed than by ordinary kriging and indicator kriging. They also showed better spatial characteristics of distribution of nodule abundance.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.273-282
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• 2003

The problem of estimating the parameters of k-population Weibull distributions is discussed under the prior of ordered scale parameters. Parameters are estimated by the Gibbs sampling method. Since the conditional posterior distribution of the shape parameter in the Gibbs sampler is not log-concave, the shape parameter is generated by the adaptive rejection sampling. Finally, we applied this estimation methodology to the data discussed in Nelson (1970).

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.9
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• pp.1335-1348
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• 1998

Flow characteristics in transitional boundary layers on a flat plate were experimentally investigated under three different freestream conditions i. e. uniform flow with 0.1 % and 3.7% freestream turbulent intensity and cylinder-wake with 3.7% maximum turbulent intensity. Instantaneous streamwise velocities in laminar, transitional and turbulent boundary layers were measured by I-type hot-wire probe. For estimation of wall shear stresses on the flat plate, measured mean velocities near the wall were applied to the principle of Computational Preston Tube Method (CPM). Distributions of skin friction coefficients were reasonably predicted in all developed boundary layers. Intermittency profiles, which were estimated using Conditional Sampling Technique in transitional boundary layers, were also consistent with previously published data. It was predicted that the incoming turbulent intensity had more influence on transition onset point and transition process than freestream turbulent intensity existed just over the transition region. It was also confirmed that non-turbulent and turbulent profiles in transitional boundary layers could not be simply treated as Blasius and fully turbulent profiles.

• Journal of Korean Association for Spatial Structures
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• v.6 no.1 s.19
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• pp.83-90
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• 2006

The GF(Gust Factor) method is usually used as a method to evaluate equivalent static wind loads for general structures. The GF method is performed on the assumption that the shape of the equivalent static wind load profile is typically similar to that of mean wind loads. The shape of fluctuating wind loads could be quite different with that of the mean wind loads in case of large-span structures. So, the effect of higher modes as well as first mode must be considered to evaluate the wind loads. In this study, the ACS (Advanced Conditional Sampling) method is suggested to evaluate of equivalent static wind loads after investigating about GF and LRC method. The An method ran derive effective static wind loads by combining wind pressures and inertia forces of a structure chosen at a maximum load effect. The maximum load effect is assessed with the time history analysis using pressure data measured in wind tunnel tests. Equivalent static wind loads evaluated using ACS, GF, and LRC methods are compared to verify the effectiveness of ACS method.

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.327-347
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• 2020

We consider a credit portfolio with highly skewed exposures. In the portfolio, small number of obligors have very high exposures compared to the others. For the Bernoulli mixture model with highly skewed exposures, we propose a new importance sampling scheme to estimate the tail loss probability over a threshold and the corresponding expected shortfall. We stratify the sample space of the default events into two subsets. One consists of the events that the obligors with heavy exposures default simultaneously. We expect that typical tail loss events belong to the set. In our proposed scheme, the tail loss probability and the expected shortfall corresponding to this type of events are estimated by a conditional Monte Carlo, which results in variance reduction. We analyze the properties of the proposed scheme mathematically. In numerical study, the performance of the proposed scheme is compared with an existing importance sampling method.