• 전자공학회논문지S
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• 제35S권4호
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• pp.105-117
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• 1998

In this paper, the general formula of disparity estimation based on Bayesian Maximum A Posteriori (MAP) algorithm is derived and implemented with simplified probabilistic models. The probabilistic models are independence and similarity among the neighboring disparities in the configuration.The formula is the generalized probabilistic diffusion equation based on Bayesian model, and can be implemented into the some different forms corresponding to the probabilistic models in the disparity neighborhood system or configuration. And, we proposed new probabilistic models in order to simplify the joint probability distribution of disparities in the configuration. According to the experimental results, the proposed algorithm outperformed the other ones, such as sum of swuared difference(SSD) based algorithm and Scharstein's method. We canconclude that the derived formular generalizes the probabilistic diffusion based on Bayesian MAP algorithm for disparity estimation, and the propsoed probabilistic models are reasonable and approximate the pure joint probability distribution very well with decreasing the computations to 0.01% of the generalized formula.

• Smart Structures and Systems
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• 제15권3호
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• pp.751-767
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• 2015

A new procedure is proposed for assessing probabilistic condition of structures considering effect of measured data uncertainty. In this procedure, multiple Finite Element (FE) models are identified by using weighting vectors that represent the uncertainty conditions of measured data. The distribution of structural parameters is analysed using a Principal Component Analysis (PCA) in relation to uncertainty conditions, and the identified models are classified into groups according to their similarity by using a K-means method. The condition of a structure is then assessed probabilistically using FE models in the classified groups, each of which represents specific uncertainty condition of measured data. Yeondae bridge, a steel-box girder expressway bridge in Korea, is used as an illustrative example. Probabilistic condition of the bridge is evaluated by the distribution of load rating factors obtained using multiple FE models. The numerical example shows that the proposed method can quantify uncertainty of measured data and subsequently evaluate efficiently the probabilistic condition of bridges.

• Geomechanics and Engineering
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• 제24권4호
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• pp.399-406
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• 2021

It is a key issue in the tunnel design to evaluate the stability of the excavation face. Two efficient analytical models in the context of the limit equilibrium method (LEM) and the limit analysis method (LAM) are used to carry out the deterministic calculations of the safety factor. The safety factor obtained by these two models agrees well with that provided by the numerical modelling by FLAC 3D, but consuming less time. A simple probabilistic approach based on the Mote-Carlo Simulation technique which can quickly calculate the probability distribution of the safety factor was used to perform the probabilistic analysis on the tunnel face stability. Both the cumulative probabilistic distribution and the probability density function in terms of the safety factor were obtained. The obtained results show the effectiveness of this probabilistic approach in the tunnel design.

• Wind and Structures
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• 제38권4호
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• pp.309-323
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• 2024

The gust factor and turbulence intensity are two crucial parameters that characterize the properties of turbulence. In tropical cyclones (TCs), these parameters exhibit significant variability, yet there is a lack of established formulas to account for their probabilistic characteristics with consideration of their inherent connection. On this condition, a probabilistic analysis of gust factors and turbulence intensities of TCs is conducted based on fourteen sets of wind data collected at the Sutong Cable-stayed Bridge site. Initially, the turbulence intensities and gust factors of recorded data are computed, followed by an analysis of their probability densities across different ranges categorized by mean wind speed. The Gaussian, lognormal, and generalized extreme value (GEV) distributions are employed to fit the measured probability densities, with subsequent evaluation of their effectiveness. The Gumbel distribution, which is a specific instance of the GEV distribution, has been identified as an optimal choice for probabilistic characterizations of turbulence intensity and gust factor in TCs. The corresponding empirical models are then established through curve fitting. By utilizing the Gumbel distribution as a template, the nexus between the probability density functions of turbulence intensity and gust factor is built, leading to the development of a generalized probabilistic model that statistically describe turbulence intensity and gust factor in TCs. Finally, these empirical models are validated using measured data and compared with suggestions recommended by specifications.

• Communications for Statistical Applications and Methods
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• 제24권1호
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• pp.67-80
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• 2017

Over the last few decades, ensemble forecasts based on global climate models have become an important part of climate forecast due to the ability to reduce uncertainty in prediction. Moreover in ensemble forecast, assessing the prediction uncertainty is as important as estimating the optimal weights, and this is achieved through a probabilistic forecast which is based on the predictive distribution of future climate. The Bayesian model averaging has received much attention as a tool of probabilistic forecasting due to its simplicity and superior prediction. In this paper, we propose a new Bayesian model averaging method for probabilistic ensemble forecasting. The proposed method combines a deterministic ensemble forecast based on a multivariate regression approach with Bayesian model averaging. We demonstrate that the proposed method is better in prediction than the standard Bayesian model averaging approach by analyzing monthly average precipitations and temperatures for ten cities in Korea.

• 한국해안·해양공학회논문집
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• 제36권1호
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• pp.20-36
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• 2024

요 지 : 본 연구에서는 먼저 우리나라 해역별 해양환경 특성이 담긴 장기 파랑 관측자료로부터 Goda 모형을 활용하여 파력과 양력 시계열자료를 생성하였다. 이어 이렇게 생성된 시계열자료부터 Three-parameter Weibull distribution에 기반한 파력과 양력 확률모형을 개발하였다. 해역별로 다른 우리나라 해양환경은 파력과 양력 확률모형 모수에서도 그 차이를 확연하게 드러내었다. 충분히 발달한 풍성 파가 우월한 남해안의 경우 큰 Scale Coefficient, 작은 Location Coefficient, 1.3 전후의 Shape Coefficient로 특정되는 것을 확인하였다. 이에 비해 파랑의 성장이 취송거리에 의해 제한되는 서해를 마주하고 있는 군산의 경우 작은 Scale Coefficient, 큰 Location Coefficient, 2.0 전후의 Shape Coefficient로 특정되었다. 서해와 남해가 만나는 해역을 마주하고 있는 목포의 경우 작은 Scale Coefficient, 큰 Location Coefficient, 제일 작은 Shape Coefficient를 지녀 남해와 서해의 해양환경이 혼재한다는 사실도 확인할 수 있었다.

• 한국해안·해양공학회논문집
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• 제32권2호
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• pp.106-121
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• 2020

항 외곽시설 신뢰성 설계가 합리적으로 구현하기 위해서는 우리나라 해양환경 특성이 반영된 확률모형이 필요하며 이러한 시각에서 본 연구에서는 천 해역 확률모형 개발을 위한 기초연구의 일부로 불규칙 파랑 천수 과정을 수치 모의하였다. 수치 모의는 자연해안에서 흔히 관측되는 사주가 원빈에 형성된 해안을 대상으로 수행하였으며 파랑모형은 spatially filtered Navier-Stokes Eq., LES[Large Eddy Simulation], one equation dynamic Smagorinsky turbulence closure 등으로 구성하였다. 불규칙 파랑은 우리나라 동해안에서 관측되는 너울 특성을 반영하기 위해 다양한 첨두 증강계수를 지니는 JONSWAP 스펙트럼과 random phase method를 사용하여 모의하였다. 파고분포의 모수는 먼저 수치 모의에서 관측된 자유수면 시계열 자료를 threshold crossing method로 파별 해석[wave by wave analysis]하여 개별 파랑을 특정하고, 이어 이렇게 특정된 파마루와 파곡 빈도 해석결과로부터 산출하였다. 모의결과 현재 천 해역 파고분포를 대표하는 수정 Glukhovskiy 파고분포는 큰 파고와 작은 파고 발생확률은 과다하게, 중간 크기 파고 발생확률은 과소하게 평가하는 것으로 모의 되었으며, 이에 반해 본 논문에서 제시된 파고분포의 경우 일치도가 상당하였다. 또한, 전술한 수정 Glukhovskiy 파고분포와의 간극은 쇄파역에서 제일 현저하게 관측되어 수정 Glukhovskiy 파고분포를 쇄파역 언저리에 거치되는 외곽시설 신뢰성 설계에 적용하는 일은 지양되어야 할 것으로 판단된다.

• 한국지진공학회논문집
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• 제19권3호
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• pp.93-102
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• 2015

This study evaluates collapse probabilities of structures which are designed according to a domestic seismic design code, KBC2009. In evaluating their collapse probabilities, to do this, probabilistic distribution models for seismic hazard and structural capacity are required. In this paper, eight major cities in Korea are selected and the demand probabilistic distribution of each city is obtained from the uniform seismic hazard. The probabilistic distribution for the structural capacity is assumed to follow a underlying design philosophy implicitly defined in ASCE 7-10. With the assumptions, the structural collapse probability in 50 years is evaluated based on the concept of a risk integral. This paper then defines an mean value of the collapse probabilities in 50 years of the selected major cities as the target risk. Risk-targeted spectral accelerations are finally suggested by modifying a current mapped spectral acceleration to meet the target risk.

• KIEE International Transactions on Electrophysics and Applications
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• 제3C권1호
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• pp.1-4
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• 2003

This paper presents an attempt to develop probabilistic multistress life models to evaluate the lifetime characteristics of epoxy-encapsulated magnet wire with heavy build polyurethane enamel. A set of accelerated life tests were conducted over a wide range of pulsating voltages, temperatures, and frequencies. Samples of fine gauge twisted pairs of the encapsulated magnet wire were tested us-ing a pulse endurance dielectric test system. An electrical-thermal lifetime function was combined with the Weibull distribution of lifetimes. The parameters of the combined Weibull-electrical-thermal model were estimated using maximum likelihood estimation. Likewise, a generalized electrical-thermal-frequency life model was also developed. The parameters of this new model were estimated using multiple linear regression technique. It was found in this paper that lifetime estimates of the two proposed probabilistic multistress life models are good enough. This suggests the suitability of using the general electrical-thermal-frequency model to estimate the lifetime of the encapsulated magnet wire over a wide range of voltages, temperatures and pulsating frequencies.

• Transactions on Electrical and Electronic Materials
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• 제18권6호
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• pp.350-358
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• 2017

Recently, owing to increased interest in low-carbon energy supplies, renewable energy sources such as photovoltaics and wind turbines in distribution networks have received considerable attention for generating clean and unlimited energy. The presence of energy storage systems (ESSs) in the promising field of active distribution networks (ADNs) would have direct impact on power system problems such as encountered in probabilistic distributed generation (DG) model studies. Hence, the optimal procedure is offered herein, in which the simultaneous placement of an ESS, photovoltaic-based DG, and wind turbine-based DG in an ADN is taken into account. The main goal of this paper is to maximize the net present value of the loss reduction benefit by considering the price of electricity for each load state. The proposed framework consists of a scenario tree method for covering the existing uncertainties in the distribution network's load demand as well as DG. The collected results verify the considerable effect of concurrent installation of probabilistic DG models and an ESS in defining the optimum site of DG and the ESS and they demonstrate that the optimum operation of an ESS in the ADN is consequently related to the highest value of the loss reduction benefit in long-term planning as well. The results obtained are encouraging.