• Earthquakes and Structures
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• 제3권6호
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• pp.869-887
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• 2012

Ground motion scaling techniques are actively debated in the earthquake engineering community. Considerations such as what amplitude, over what period range and to what target spectrum are amongst the questions of practical importance. In this paper, the effect of various ground motion scaling approaches are explored using three reinforced concrete prototypical building models of 8, 12 and 20 stories designed to respond nonlinearly under a design level earthquake event in the seismically active Southern California region. Twenty-one recorded earthquake motions are selected using a probabilistic seismic hazard analysis and subsequently scaled using four different strategies. These motions are subsequently compared to spectrally compatible motions. The nonlinear response of a planar frameidealized building is evaluated in terms of plasticity distribution, floor level acceleration and uncorrelated acceleration amplification ratio distributions; and interstory drift distributions. The most pronounced response variability observed in association with the scaling method is the extent of higher mode participation in the nonlinear demands.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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• pp.340-343
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• 2003

This study presents a practical procedure for the Bayesian inversion of geophysical data by Markov chain Monte Carlo (MCMC) sampling and geostatistics. We have applied geostatistical techniques for the acquisition of prior model information, and then the MCMC method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter. This approach provides an effective way to treat Bayesian inversion of geophysical data and reduce the non-uniqueness by incorporating various prior information.

• Earthquakes and Structures
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• 제7권2호
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• pp.201-216
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• 2014

In this paper the vulnerability of the confined masonry buildings is evaluated analytically. The proposed approach includes the nonlinear dynamic analysis of the two-story confined masonry buildings with common plan as a reference structure. In this approach the damage level is calculated based on the probability of exceedance of loss vs a specified ground motion in the form of fragility curves. The fragility curves of confined masonry wall buildings are presented in two levels of limit states corresponding to elastic and maximum strength versus PGA based on analytical method. In this regard the randomness of parameters indicating the characteristics of the building structure as well as ground motion is considered as likely uncertainties. In order to develop the analytical fragility curves the proposed analytical models of confined masonry walls in a previous investigation of the authors, are used to specify the damage indices and responses of the structure. In order to obtain damage indices a series of pushover analyses are performed, and to identify the seismic demand a series of nonlinear dynamic analysis are conducted. Finally by considering various mechanical and geometric parameters of masonry walls and numerous accelerograms, the fragility curves with assuming a log normal distribution of data are derived based on capacity and demand of building structures in a probabilistic approach.

• Computers and Concrete
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• 제14권1호
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• pp.19-40
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• 2014

Reinforced concrete deep beams are structural beams with low shear span-to-depth ratio, and hence in which the strain distribution is significantly nonlinear and the conventional beam theory is not applicable. A strut-and-tie model is considered one of the most rational and simplest methods available for shear strength prediction and design of deep beams. The strut-and-tie model approach describes the shear failure of a deep beam using diagonal strut and truss mechanism: The diagonal strut mechanism represents compression stress fields that develop in the concrete web between diagonal cracks of the concrete while the truss mechanism accounts for the contributions of the horizontal and vertical web reinforcements. Based on a database of 406 experimental observations, this paper proposes a new strut-and-tie-model for accurate prediction of shear strength of reinforced concrete deep beams, and further improves the model by correcting the bias and quantifying the scatter using a Bayesian parameter estimation method. Seven existing deterministic models from design codes and the literature are compared with the proposed method. Finally, a limit-state design formula and the corresponding reduction factor are developed for the proposed strut-andtie model.

• Wind and Structures
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• 제38권4호
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• pp.277-293
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• 2024

The recorded thunderstorm winds at a point contain tri-directional components. The probabilistic characteristics of such recorded winds in terms of instantaneous mean wind speed and direction, and the probability distribution and the time-frequency dependent crossed and non-crossed power spectral density functions for the high-frequency fluctuating wind components are unclear. In the present study, we analyze the recorded tri-directional thunderstorm wind components by separating the recorded winds in terms of low-frequency time-varying mean wind speed and high-frequency fluctuating wind components in the alongwind direction and two orthogonal crosswind directions. We determine the time-varying mean wind speed and direction defined by azimuth and elevation angles, and analyze the spectra of high-frequency wind components in three orthogonal directions using continuous wavelet transforms. Additionally, we evaluate the coherence between each pair of fluctuating winds. Based on the analysis results, we develop empirical spectral models and lagged coherence models for the tri-directional fluctuating wind components, and we indicate that the fluctuating wind components can be treated as Gaussian. We show how they can be used to generate time histories of the tri-directional thunderstorm winds.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제27권3호
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• pp.137-155
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• 2020

Redundancy is commonly employed to improve system reliability. In most situations, components in the standby configurations are assumed statistically similar but independent. In many realistic models, all parts in standby are not treated as identical as they have different failure possibilities. The operational structure of the system has subsystem-1 with five identical components working under 2-out-of-5: G; policy, and the subsystem-2 has two units and functioning under 1-out-of-2: G; policy. Failure rates of units of subsystems are constant and assumed to follow an exponential distribution. Computed results give a new aspect to the scientific community to adopt multi-dimension repair in the form of the copula.

• 대한산업공학회지
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• 제26권3호
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• pp.193-199
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• 2000

In many studies, considerable attention has been focussed upon choosing a model which represents underlying process of time series and forecasting the future. In the real world, however, there may be some cases that one model can not reflect all the characteristics of original time series. Under such circumstances, we may get better performance by combining the forecasts from several models. The most popular methods for combining forecasts involve taking a weighted average of multiple forecasts. But the weights are usually unstable. In cases the assumptions of normality and unbiasedness for forecast errors are satisfied, a Bayesian method can be used for updating the weights. In the real world, however, there are many circumstances the Bayesian method is not appropriate. This paper proposes a PNN(Probabilistic Neural Net) approach as a method for combining forecasts that can be applied when the assumption of normality or unbiasedness for forecast errors is not satisfied. In this paper, PNN method, which is similar to Bayesian approach, is suggested as an updating method of the unstable weights in the combination of the forecasts. The PNN method has been usually used in the field of pattern recognition. Unlike the Bayesian approach, it requires no assumption of a specific prior distribution because it gets probabilities by using the distribution estimated from given data. Empirical results reveal that the PNN method offers superior predictive capabilities.

• 대한조선학회논문집
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• 제56권2호
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• pp.161-167
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• 2019

In general, fatigue analysis is performed by using deterministic model to estimate the optimal parameters. However, the deterministic model is difficult to clearly describe the physical phenomena of fatigue failure that contains many uncertainty factors. With regard to this, efforts have been made in this research to compare with the deterministic model and the stochastic models. Firstly, One deterministic S-N curve was derived from ordinary least squares technique and two P-S-N curves were estimated through Bayesian-linear regression model and Markov-Chain Monte Carlo simulation. Secondly, the distribution of Long-term fatigue damage and fatigue life were predicted by using the parameters obtained from the three methodologies and the long-term stress distribution.

• 방사성폐기물학회지
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• 제12권3호
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• pp.191-198
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• 2014

가상의 심지층 처분 부지에서 이루어진 지하수 유동 모의 결과를 이용하여 처분 심도의 지하수 유량 분포를 분석하고 그 결과를 처분 안전성 평가에 이용할 수 있는 방안을 제시하였다. 처분 심도의 지하수 유동량은 가상의 처분 부지를 대상으로 한 광역 및 국지적 지하수 유동 모의 결과의 지하수두 분포를 이용하여 분석하였다. 지하수 유동량 분포를 이용하여 처분공 위치의 지하수 유동량을 분석하고 최대값을 기준으로 지하수 유동량을 표준화하여 처분공에서의 처분 용기 파손 가능성을 확률적으로 도시하였다. 확률적으로 제시된 처분 용기의 파손 가능성을 이용하여, 처분 용기로부터 누출이 일어날 것으로 가정된 위치에서 지표 환경으로 이동하는 방사성 핵종의 이동량에 대한 확률론적 기대값을 계산하여 결정론적으로 평가된 이전 연구 결과와 비교하였다. 이런 평가 방법은 현장 조건을 더욱 많이 반영할 수 있는 안전성 평가 방안 구축에 기여할 수 있을 것으로 생각된다.

• 한국전산구조공학회논문집
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• 제32권3호
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• pp.173-181
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• 2019

제한된 실험 데이터로부터 확률분포함수를 추정하기 위해서 KDE가 많이 사용되고 있다. KDE에 의한 분포함수는 대역폭 선택법에 따라서 실험 데이터에 대해 평활하거나 과대적합된 커널 추정치를 생성한다. 본 연구에서는 Silverman's rule of thumb, rule using adaptive estimate, oversmoothing rule을 사용해서 각 방법에 따른 정확성과 보수적인 성향을 비교하였다. 비교를 위해서 단봉분포와 다봉분포를 가지는 실제 모델을 가정하고 통계적 시뮬레이션을 수행한 다음 다양한 데이터의 개수에 따른 추정된 분포함수의 정확도와 보수성을 비교하였다. 또한, 간단한 신뢰성 예제를 통해 대역폭 선택법에 따른 KDE의 추정된 분포가 신뢰성 해석 결과에 어떻게 영향을 미치는지 확인하였다.