• Journal of the Korean Geotechnical Society
• /
• v.35 no.12
• /
• pp.45-58
• /
• 2019

In this study, a stochastic analysis procedure based on numerical analysis was proposed to evaluate a kind of intensity-duration rainfall threshold for the initiation of slope failure due to rainfall infiltration. Fragility curves were generated as a function of rainfall intensity-duration from the results of probabilistic slope stability analysis by MCS considering the uncertainty of the soil shear strength, reflecting the results of infiltration analysis of rainfall over time. In the probabilistic analysis, slope stability analyses combined with the infiltration analysis of rainfall were performed to calculate the limit state function. Using the derived fragility curves, a chart showing the relationship between rainfall intensity and slope failure-time was developed. It is based on a probabilistic analysis considering the uncertainty of the soil properties. The proposed probabilistic failure distribution analysis could be beneficial for analyzing the time-dependent failure process of soil slopes due to rainfall infiltration, and for predicting when the slope failure should occur.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.268-268
• /
• 2022

지진해일은 발생빈도는 높지 않지만, 한 번 발생하게 되면 막대한 피해를 일으킬 수 있다. 우리나라에서는 1,900년대 4건의 지진해일이 기록되었으며, 이로 인해 동해안 및 남해안 등에 인명피해 및 재산피해가 발생하였다. 또한 2011년 동일본 지진해일로 인해 후쿠시마 원자력 발전소 변전설비가 침수됨에 따라 냉각수 공급이 중단되고 방화벽이 파괴되어 방사능이 누출되어 큰 피해로 연결되었다. 이러한 피해를 저감하기 위해 지진해일 수치해석과 확률론적 분석방법 등 다양한 방법을 활용한 연구가 국내외 적으로 활발히 수행되고 있다. 본 연구는 확률분포기반 지진해일고 예측모델 개발을 위해 수치해석을 수행하여 지진해일고(tsunami heights)를 산출하고 결과값에 대한 적절한 확률분포 분석을 실시하는 것이다. 지진해일고는 원자력발전소에서 취수구를 통한 냉각수 공급가능 여부를 판단하기 위해 최대 지진해일고(maximum tsunami height)와 최저 지진해일고(minimum tsunami height)로 구분하였다. 지진해일 수치해석은 지진원(단층매개변수) 조사, 조사된 지진원 중 지진해일 수치해석 case 선정을 위한 파향선추적기법(wave ray tracing) 수행, 선정된 지진원에 대해 로직트리(logic tree) 기법 적용, 로직트리를 적용한 지진원 case에 대한 수치해석 순서로 수행하였다. 수치해석을 통해 산출된 최대 및 최저 지진해일고 자료를 기반으로 확률분포형을 선정하기 위하여 확률분포별 적합성 평가를 실시하였다. 선정된 분포를 기준으로 처오름 및 처내림높이와 관련된 다양한 변수간의 의존관계를 파악하였다. 향후, 파악된 의존관계를 기반으로 예측모델을 개발하여 수치해석 결과와 연계함으로써 국내에 적용할 수 있는 확률론적 지진해일재해도를 제시할 수 있을 것으로 판단된다.

• Journal of the Korean Institute of Gas
• /
• v.21 no.3
• /
• pp.61-69
• /
• 2017

The commercial development of unconventional gas is pursued in North America because it is more feasible owing to the technology required to improve productivity. Shale reservoir have low permeability and gas production can be carried out through cracks generated by hydraulic fracturing. The decline rate during the initial production period is high, but very low latter on, there are significant variations from the initial production behavior. Therefore, in the prediction of the production rate using deterministic decline curve analysis(DCA), it is not possible to consider the uncertainty in the production behavior. In this study, production rate of the Eagle Ford shale is predicted by Arps Hyperbolic and Modified SEPD. To minimize the uncertainty in predicting the Estimated Ultimate Recovery(EUR), Monte Carlo simulation is used to multi-wells analysis. Also, kernel density function is applied to determine probability distribution of decline curve factors without any assumption.

• Journal of Korea Water Resources Association
• /
• v.44 no.10
• /
• pp.843-851
• /
• 2011

In hydrology, it is appropriate to use probabilistic method for forecasting mid/long term streamflow due to the uncertainty of input data. Through this study, it is expanded mid/long term forecasting system more effectively adding priory process function based on PDF-ratio method to the RRFS-ESP system for Guem River Basin. For implementing this purpose, weight is estimated using probabilistic weather forecasting information from KMA. Based on these results, ESP probability is updated per scenario. Through the estimated result per method, the average forecast score using ESP method is higher than that of naive forecasting and it confirmed that ESP method results in appropriate score for RRFS-ESP system. It is also shown that the score of ESP method applying revised inflow scenario using probabilistic weather forecasting is higher than that of ESP method. As a results, it will be improved the accuracy of forecasting using probabilistic weather forecasting.

• Journal of the Korean Geotechnical Society
• /
• v.34 no.5
• /
• pp.37-51
• /
• 2018

The slope failure due to the rainfall infiltration occurs frequently in Korea, since the depth of the weathered residual soil layer is shallow in mountainous region. Depth of the failure surface is shallow and tends to pass near the interface between impermeable bedrock and soil layer. Soil parameters that have a significant impact on the instability of unsaturated slopes due to rainfall infiltration inevitably include large uncertainties. Therefore, this study proposes a probabilistic analysis procedure by Monte Carlo Simulation which considers the hydraulic characteristics and strength characteristics of soil as random variables in order to predict slope failure due to rainfall infiltration. The Green-Ampt infiltration model was modified to reflect the boundary conditions on the slope surface according to the rainfall intensity and the boundary condition of the shallow impermeable bedrock was introduced to predict the stability of unsaturated soil slope with shallow bedrock under constant rainfall intensity. The results of infiltration analysis were used as inputs of infinite slope analysis to calculate the safety factor. The proposed analysis method can be used to calculate the time-dependent failure probability of soil slope due to rainfall infiltration.

• Nuclear Engineering and Technology
• /
• v.19 no.4
• /
• pp.233-241
• /
• 1987

Difficulties are encountered when the behavior of complex systems (i.e., fuel failure probability) that have unreliable deterministic models is predicted. For more realistic prediction of the behavior of complex systems with limited observational data, the present study was undertaken to devise an approach of combining predictions from the deterministic model and actual observational data. Predictions by this method of combining are inferred to be of higher reliability than separate predictions made by either model taken independently. A systematic method of hierarchical pattern discovery based on the method developed in the SPEAR was used for systematic search of weighting factors and pattern boundaries for the present method. A sample calculation was performed for prediction of CANDU fuel failures that had occurred due to power ramp during refuelling process. It was demonstrated by this sample calculation that there exists a region of feature space in which fuel failure probability from the PROFIT model nearly agree with that from observational data.

• The Journal of Engineering Geology
• /
• v.32 no.3
• /
• pp.327-338
• /
• 2022

This study aims to empirically and statistically predict soil depths across areas affected by landslides. Using soil depth measurements from a landslide area in Korea, two sets of soil depths are calculated using a Z-model based on terrain elevation and a probabilistic statistical model. Both sets of calculation results are applied to derive landslide risk using the saturated infiltration depth ratio of the soil layer. This facilitates analysis of the infiltration of rainfall into soil layers for a rainfall event. In comparison with the probabilistic statistical model, the Z-model yields soil depths that are closer to measured values in the study area. Landslide risk assessment in the study area based on soil depth predictions from the two models shows that the percentage of first-grade landslide risk assessed using soil depths from the probabilistic statistical model is 2.5 times that calculated using soil depths from the Z-model. This shows that soil depths directly affect landslide risk assessment; therefore, the acquisition and application of local soil depth data are crucial to landslide risk analysis.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.14 no.5
• /
• pp.119-127
• /
• 2010

This paper provides a new approach for durability prediction of reinforced concrete structures exposed to carbonation. In this method, the prediction can be updated successively by a Bayes' theorem when additional data are available. The stochastic properties of model parameters are explicitly taken into account in the model. To simplify the procedure of the model, the probability of the durability limit is determined based on the samples obtained from the Latin Hypercube Sampling(LHS) technique. The new method may be very useful in design of important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored. For using the new method, in which the prior distribution is developed to represent the uncertainties of the carbonation velocity using data of concrete structures(3700 specimens) in Korea and the likelihood function is used to monitor in-situ data. The posterior distribution is obtained by combining a prior distribution and a likelihood function. Efficiency of the LHS technique for simulation was confirmed through a comparison between the LHS and the Monte Calro Simulation(MCS) technique.

• Journal of the Society of Naval Architects of Korea
• /
• v.57 no.1
• /
• pp.1-7
• /
• 2020

In general, an inspection schedule is established based on the long-term fatigue life during the design stage. However, in the design stage, it is difficult to clearly identify the uncertainty factors affecting long-term fatigue life. In this study, the probabilistic fatigue life assessment was conducted in accordance with the methodology of DNV-GL. Firstly, The initial crack distribution estimated through the initial crack propagation analysis was updated by reflecting the results of crack inspection. Secondly, the updated crack distribution was compared with the initial crack distribution, and the probability of failure was updated with the effect of crack inspection.

• Journal of Ocean Engineering and Technology
• /
• v.5 no.2
• /
• pp.191-191
• /
• 1991