• 제목/요약/키워드: damage probabilities

검색결과 67건 처리시간 0.028초

추계학적 위너 확률과정을 이용한 경사제의 실시간 피해경로 추적과 잔류수명 추정 (Estimation of Residual Useful Life and Tracking of Real-time Damage Paths of Rubble-Mound Breakwaters Using Stochastic Wiener Process)

  • 이철응
    • 한국해안·해양공학회논문집
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    • 제32권3호
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    • pp.147-160
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    • 2020
  • 추계학적 WP을 이용하여 불확실성을 고려하면서 항만 구조물의 실시간에 따른 피해와 파괴확률 그리고 잔류수명을 해석할 수 있는 모형을 수립하였다. 과거부터 현재까지의 피해상태와 미래에 발생될 피해 진행 과정에 포함되는 불확실성을 고려할 수 있는 추계학적 확률모형이다. 피해경로를 추적할 수 있으며 누적피해의 밀도함수도 산정하여 파괴확률을 추정할 수 있다. 또한 구조물의 잔류수명에 대한 밀도함수도 구할 수 있다. 최소자승법과 최우도법을 이용하여 모형의 파라미터를 추정할 수 있는 방법도 제시하였다. 검증을 위해 시간의 진행에 따른 누적피해와 잔류수명에 대한 밀도함수를 산정하고 해석하였는데 이론적인 결과가 MCS 기법의 수치적인 결과와 매우 잘 일치하였다. 또한 내구수명이나 잔류수명에 대한 밀도함수의 거동과 MTTF와 MRL이 정량적으로 잘 일치하였다. 한편 본 연구에 수립된 모형을 경사제에 적용하기 위하여 피복재 피해에 대한 수리모형 실험자료를 활용하여 모형의 파라미터들을 추정하였다. 시간의 진행에 따른 피복재 누적피해의 밀도함수와 파괴확률을 산정하였는데 MCS의 결과와 이론적인 결과가 매우 잘 일치하였다. 경과시간이 클수록 밀도함수가 우측으로 이동하면서 불확실성이 커지면서 파괴확률이 급격하게 증가하였다. 또한 재령에 따른 잔류수명의 거동특성을 해석하였는데, 잔류수명의 분포함수에서 좌측보다는 우측 꼬리 부분이 길게 형성되어 MRL이 급격하게 감소하는 경향을 보였다. 이는 경사제 피복재의 피해가 완만하게 증가하는 현상을 반영한 것으로 판단된다. 특히 재령과 내구수명 그리고 잔류수명의 관계를 해석하였는데, 재령이 오래될수록 재령과 MRL의 합이 MTTF와 큰 차이를 보이고 있다. 이는 재령이 증가하면 잔류수명의 평균인 MRL이 불확실성에 의하여 급격히 감소하기 때문이다.

공간 예측 모델을 이용한 산사태 재해의 인명 위험평가 (Life Risk Assessment of Landslide Disaster Using Spatial Prediction Model)

  • 장동호
    • 환경영향평가
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    • 제15권6호
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    • pp.373-383
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    • 2006
  • The spatial mapping of risk is very useful data in planning for disaster preparedness. This research presents a methodology for making the landslide life risk map in the Boeun area which had considerable landslide damage following heavy rain in August, 1998. We have developed a three-stage procedure in spatial data analysis not only to estimate the probability of the occurrence of the natural hazardous events but also to evaluate the uncertainty of the estimators of that probability. The three-stage procedure consists of: (i)construction of a hazard prediction map of "future" hazardous events; (ii) validation of prediction results and estimation of the probability of occurrence for each predicted hazard level; and (iii) generation of risk maps with the introduction of human life factors representing assumed or established vulnerability levels by combining the prediction map in the first stage and the estimated probabilities in the second stage with human life data. The significance of the landslide susceptibility map was evaluated by computing a prediction rate curve. It is used that the Bayesian prediction model and the case study results (the landslide susceptibility map and prediction rate curve) can be prepared for prevention of future landslide life risk map. Data from the Bayesian model-based landslide susceptibility map and prediction ratio curves were used together with human rife data to draft future landslide life risk maps. Results reveal that individual pixels had low risks, but the total risk death toll was estimated at 3.14 people. In particular, the dangerous areas involving an estimated 1/100 people were shown to have the highest risk among all research-target areas. Three people were killed in this area when landslides occurred in 1998. Thus, this risk map can deliver factual damage situation prediction to policy decision-makers, and subsequently can be used as useful data in preventing disasters. In particular, drafting of maps on landslide risk in various steps will enable one to forecast the occurrence of disasters.

고층 RC 벽식 건물의 지진 취약도 분석 (Seismic Fragility Analysis of High-Rise RC Box-Type Wall Building Structures)

  • 정기현;이한선;황경란;권오성;김승직
    • 한국지진공학회논문집
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    • 제20권3호
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    • pp.155-162
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    • 2016
  • Observations of the damages to high-rise reinforced concrete (RC) wall building structures caused by by recent earthquakes in Chile ($M_w$ 8.8, February 2010) and New Zealand (February 2011, $M_L$ 6.3) have generally exceeded expectations. Firstly, this study estimated the seismic damage levels of 15-story RC box-type wall building structures using the analytical models calibrated by the results of a shaking table test on a 1:5 scale 10-story RC box-type wall building model. Then, the seismic fragility analysis of the prototype model was conducted by using the SAC/FEMA method and the incremental dynamic analysis (IDA). To compensate for the uncertainties and variability of ground motion and its impacts on the prototype model, in the SAC/FEMA method, a total of 61 ground motion records were selected from 20 earthquakes, with a magnitude ranging from 5.9 to 8.8 and an epicentral distance ranging from 5 to 105km. In the IDA, a total of 11 ground motion records were used based on the uniform hazard response spectrum representing a return period of 2,475 years. As a result, the probabilities that the limits of the serviceability, damage control, and collapse prevention would be exceeded were as follows: from the SAC/FEMA method: 79%, 0.3%, and 0%, respectively; and from the IDA: 57%, 1.7%, and 0%, respectively.

Changes in Biston robustum and Camellia japonica distributions, according to climate change predictions in South Korea

  • Kim, Tae Guen;Han, Yong-Gu;Jeong, Jong Chul;Kim, Youngjin;Kwon, Ohseok;Cho, Youngho
    • Journal of Ecology and Environment
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    • 제38권3호
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    • pp.327-334
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    • 2015
  • We investigated the current and potential spatial distributions and habitable areas of Biston robustum and Camellia japonica in South Korea in order to provide useful data for the conservation of C. japonica and minimize the damage caused by B. robustum. It was predicted that, by 2070, although B. robustum would be widely distributed throughout the Korean Peninsula, except for the western and eastern coastal areas, it would be narrowly distributed along the Sokcho-si and Goseong-gun coastlines in Gangwon Province. C. japonica is currently located along the southern coastline but its critical habitable area is predicted to gradually disappear by 2070. Assessment of the potential distribution probabilities of B. robustum and C. japonica revealed that the area under the curve (AUC) values were 0.995 and 0.991, respectively, which indicate high precision and applicability of the model. Major factors influencing the potential distribution of B. robustum included precipitation of wettest quarter and annual precipitation (BIO16 and BIO12), whereas annual mean temperature and mean temperature of wettest quarter (BIO1 and BIO8) were important variables for explaining C. japonica distribution. Overlapping areas of B. robustum and C. japonica were $11,782km^2$, $5447km^2$, and $870km^2$ for the current, 2050-predicted, and 2070-predicted conditions, respectively, clearly showing a dramatic decrease in area. Although it is predicted that B. robustum would cause continuous damage to C. japonica in the southern part of the Korean Peninsula, such impacts might diminish over time and become negligible in the future.

관개용저수지 용수공급지수(IRWSI)의 확률통계 분석 (Statistical Analysis of Irrigation Reservoir Water Supply Index)

  • 김선주;이광야;강상진
    • 한국농공학회지
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    • 제40권4호
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    • pp.58-66
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    • 1998
  • Irrigation Reservoir Water Supply Index(IRWSI), which can be applied to the effective supply and management of the irrigation water resources, was developed. IRWSI was formulated as resealed nonexceedance probabilities of two hydrologic components : reservoir storage ratio and precipitation. To generate nonexceedance probability of hydrologic component, it was important to define the optimal one among the various probability distribution function in the state of nature. To define an optimal probability distribution, in this study, four types of probability distribution function were tested by the K-S fitting, and for the calculation of IRWSI, reservoir storage ratio(%) and precipitation used Normal distribution & Gamma distribution, respectively. In this study, the weight coefficients of a and b for each hydrologic component, which is precipitation and reservoir storage ratio, was decided as 0.8 and 0.2, respectively. While some studies changed weight coefficients according to the size of basin area, this study used same values without considering that. From the analysis of drought characteristics, it was found that the IRWSI was sensitive to the size of irrigation area rather than the size of basin area, and the south-eastern region of Korea had been suffered from severe drought damage.

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Probabilistic seismic performance evaluation of non-seismic RC frame buildings

  • Maniyar, M.M.;Khare, R.K.;Dhakal, R.P.
    • Structural Engineering and Mechanics
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    • 제33권6호
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    • pp.725-745
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    • 2009
  • In this paper, probabilistic seismic performance assessment of a typical non-seismic RC frame building representative of a large inventory of existing buildings in developing countries is conducted. Nonlinear time-history analyses of the sample building are performed with 20 large-magnitude medium distance ground motions scaled to different levels of intensity represented by peak ground acceleration and 5% damped elastic spectral acceleration at the first mode period of the building. The hysteretic model used in the analyses accommodates stiffness degradation, ductility-based strength decay, hysteretic energy-based strength decay and pinching due to gap opening and closing. The maximum inter story drift ratios obtained from the time-history analyses are plotted against the ground motion intensities. A method is defined for obtaining the yielding and collapse capacity of the analyzed structure using these curves. The fragility curves for yielding and collapse damage levels are developed by statistically interpreting the results of the time-history analyses. Hazard-survival curves are generated by changing the horizontal axis of the fragility curves from ground motion intensities to their annual probability of exceedance using the log-log linear ground motion hazard model. The results express at a glance the probabilities of yielding and collapse against various levels of ground motion intensities.

Multi-unit Level 2 probabilistic safety assessment: Approaches and their application to a six-unit nuclear power plant site

  • Cho, Jaehyun;Han, Sang Hoon;Kim, Dong-San;Lim, Ho-Gon
    • Nuclear Engineering and Technology
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    • 제50권8호
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    • pp.1234-1245
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    • 2018
  • The risk of multi-unit nuclear power plants (NPPs) at a site has received considerable critical attention recently. However, current probabilistic safety assessment (PSA) procedures and computer code do not support multi-unit PSA because the traditional PSA structure is mostly used for the quantification of single-unit NPP risk. In this study, the main purpose is to develop a multi-unit Level 2 PSA method and apply it to full-power operating six-unit OPR1000. Multi-unit Level 2 PSA method consists of three steps: (1) development of single-unit Level 2 PSA; (2) extracting the mapping data from plant damage state to source term category; and (3) combining multi-unit Level 1 PSA results and mapping fractions. By applying developed multi-unit Level 2 PSA method into six-unit OPR1000, site containment failure probabilities in case of loss of ultimate heat sink, loss of off-site power, tsunami, and seismic event were quantified.

On the use of time-dependent success criteria within risk-informed analyses. Application to LONF-ATWS sequences in PWR reactors

  • Jorge Sanchez-Torrijos;Cesar Queral;Carlos Paris;Maria Jose Rebollo;Miguel Sanchez-Perea;Jose Maria Posada
    • Nuclear Engineering and Technology
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    • 제54권12호
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    • pp.4601-4619
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    • 2022
  • The classical Probabilistic Safety Analysis (PSA) does not include any time dependence explicitly. However, the success criteria (SC) could evolve during the cycle for some initiating events. In that sense, there is a type of sequence in which this time-dependency is quite important, the family of Anticipated Transient without Scram (ATWS) sequences in Pressurized Water Reactors. Therefore, a new risk-informed approach is proposed in this paper, which makes it possible to obtain the time-dependent SC evolution of the safety functions affected by the Moderator Temperature Coefficient (MTC) value. Then, the evolution of the ATWS conditional core damage probability (CCDP) could be obtained using a PSA model. To quantify the CCDP, the average values of the time-dependent failure probabilities must be computed. Finally, the comparison between the CCDP obtained through the application of the classical PSA approach and the new one makes it possible to quantify the impact of time-dependence on the SC of the headers that this new risk-informed ATWS approach can provide.

Comparison of event tree/fault tree and convolution approaches in calculating station blackout risk in a nuclear power plant

  • Man Cheol Kim
    • Nuclear Engineering and Technology
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    • 제56권1호
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    • pp.141-146
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    • 2024
  • Station blackout (SBO) risk is one of the most significant contributors to nuclear power plant risk. In this paper, the sequence probability formulas derived by the convolution approach are compared with those derived by the conventional event tree/fault tree (ET/FT) approach for the SBO situation in which emergency diesel generators fail to start. The comparison identifies what makes the ET/FT approach more conservative and raises the issue regarding the mission time of a turbine-driven auxiliary feedwater pump (TDP), which suggests a possible modeling improvement in the ET/FT approach. Monte Carlo simulations with up-to-date component reliability data validate the convolution approach. The sequence probability of an alternative alternating current diesel generator (AAC DG) failing to start and the TDP failing to operate owing to battery depletion contributes most to the SBO risk. The probability overestimation of the scenario in which the AAC DG fails to run and the TDP fails to operate owing to battery depletion contributes most to the SBO risk overestimation determined by the ET/FT approach. The modification of the TDP mission time renders the sequence probabilities determined by the ET/FT approach more consistent with those determined by the convolution approach.

Optimizing shallow foundation design: A machine learning approach for bearing capacity estimation over cavities

  • Kumar Shubham;Subhadeep Metya;Abdhesh Kumar Sinha
    • Geomechanics and Engineering
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    • 제37권6호
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    • pp.629-641
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    • 2024
  • The presence of excavations or cavities beneath the foundations of a building can have a significant impact on their stability and cause extensive damage. Traditional methods for calculating the bearing capacity and subsidence of foundations over cavities can be complex and time-consuming, particularly when dealing with conditions that vary. In such situations, machine learning (ML) and deep learning (DL) techniques provide effective alternatives. This study concentrates on constructing a prediction model based on the performance of ML and DL algorithms that can be applied in real-world settings. The efficacy of eight algorithms, including Regression Analysis, k-Nearest Neighbor, Decision Tree, Random Forest, Multivariate Regression Spline, Artificial Neural Network, and Deep Neural Network, was evaluated. Using a Python-assisted automation technique integrated with the PLAXIS 2D platform, a dataset containing 272 cases with eight input parameters and one target variable was generated. In general, the DL model performed better than the ML models, and all models, except the regression models, attained outstanding results with an R2 greater than 0.90. These models can also be used as surrogate models in reliability analysis to evaluate failure risks and probabilities.