• Title/Summary/Keyword: probabilistic statistical model

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A software tool for integrated risk assessment of spent fuel transportation and storage

  • Yun, Mirae;Christian, Robby;Kim, Bo Gyung;Almomani, Belal;Ham, Jaehyun;Lee, Sanghoon;Kang, Hyun Gook
    • Nuclear Engineering and Technology
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    • v.49 no.4
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    • pp.721-733
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    • 2017
  • When temporary spent fuel storage pools at nuclear power plants reach their capacity limit, the spent fuel must be moved to an alternative storage facility. However, radioactive materials must be handled and stored carefully to avoid severe consequences to the environment. In this study, the risks of three potential accident scenarios (i.e., maritime transportation, an aircraft crashing into an interim storage facility, and on-site transportation) associated with the spent fuel transportation process were analyzed using a probabilistic approach. For each scenario, the probabilities and the consequences were calculated separately to assess the risks: the probabilities were calculated using existing data and statistical models, and the consequences were calculated using computation models. Risk assessment software was developed to conveniently integrate the three scenarios. The risks were analyzed using the developed software according to the shipment route, building characteristics, and spent fuel handling environment. As a result of the risk analysis with varying accident conditions, transportation and storage strategies with relatively low risk were developed for regulators and licensees. The focus of this study was the risk assessment methodology; however, the applied model and input data have some uncertainties. Further research to reduce these uncertainties will improve the accuracy of this model.

Analysis of Consolidation considering Uncertainties of Geotechnical Parameters and Reliability method (지반특성의 불확실성과 신뢰성 기법을 고려한 압밀해석)

  • Lee, Kyu-Hwan
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.11 no.4
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    • pp.138-146
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    • 2007
  • Geotechnical performance at the soft ground is strongly dependent on the properties of the soil beneath and adjacent to the structure of interest. These soil properties can be described using deterministic and/or probabilistic models. Deterministic models typically use a single discrete descriptor for the parameter of interest. Probabilistic models describe parameters by using discrete statistical descriptors or probability distribution density functions. The consolidation process depends on several uncertain parameters including the coefficients of consolidation and coefficients of permeability in vertical and horizontal directions. The implication of this uncertain parameter in the design of prefabricated vertical drains for soil improvement is discussed. A sensitivity analysis of the degree of consolidation and calculation of settlements to these uncertain parameters is presented for clayey deposits.

Statistical Evaluation for Residual Strength of Impacted Composite Materials (충격손상 복합재료의 잔류강도저하거동에 대한 통계적 평가)

  • Kang, Ki-Weon;Lee, Seung-Pyo;Lee, Jin-Soo;Koh, Byung-Kab
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.2
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    • pp.426-434
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    • 2010
  • This study is experimentally performed to evaluate the strength reduction behavior and its statistical properties of plain woven glass/epoxy composites. The results indicate that the major impact damage of plain woven glass/epoxy composites is the fiber breakage and matrix crack, whereas the dominant impact damage of unidirectional carbon/epoxy laminates is the delamination, which depends on the stacking sequence. The residual strength prediction models, previously proposed on unidirectional laminates, are applied to evaluate the residual strength of plain woven glass/epoxy composites with impact damage. Among these models, the results by Caprino and Avva's model have a good agreement with the experimental results. To investigate the variability of residual strength of the impacted composite materials, a statistical model was proposed and its results were in conformance with the experimental results regardless of their thickness.

Statistical Characteristic of Mechanical Properties of Concrete (콘크리트 역학적 성질의 통계적 특성)

  • Kim, Jee-Sang;Shin, Jeong-Ho;Choi, Yeon-Wang;Moon, Jea-Heum;Kim, Joo-Hyung
    • Proceedings of the Korea Concrete Institute Conference
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    • 2008.11a
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    • pp.657-660
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    • 2008
  • The mechanical properties of concrete such as compressive strength, tensile strength, and modulus of elasticity, are considerably influenced by various factors including locality. The material property prescriptions in national concrete design codes should reflect them. In Korea, they have not been studied systematically yet. A new performance-based design code is being prepared in Korea as a government-supported project and it has a plan to make new material prescriptions adopting domestic research results. As a starting point for the research on material properties, the statistical characteristics of mechanical properties of concrete are studied. In this paper, a probabilistic model of compressive strength, relationship between compressive strength and splitting tensile strength and compressive strength and elastic modulus are proposed based on experimental data.

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Probabilistic Approach to Government Employee Pension System (공무원연금제도에 대한 확률적 고찰)

  • Kim, Joo-Yoo;Song, Seong-Joo
    • Communications for Statistical Applications and Methods
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    • v.16 no.4
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    • pp.557-572
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    • 2009
  • This article examines the financial soundness of the government employee pension system(GEPS). We use a model that simplifies the existing GEPS considering survival probability distribution of the life of employees. Two approaches were selected for the research: One is the expected net value of pension for an individual employee and the other is the default probability of the system from Monte-carlo simulation. The outcome reveals following three possibilities. First of all, the individual expected net value presents unfairness between the retiree's premium and the benefit he/she receives. Secondly, the Monte-carlo simulation suggests that the default is highly likely to happen in less than 30 years. Thirdly, the governmental reserve and subsidy for GEPS should be required to a certain degree in order to alleviate the probability of default less than 5 percent for the next 30 years.

Unsupervised Semantic Role Labeling for Korean Adverbial Case (비지도 학습을 기반으로 한 한국어 부사격의 의미역 결정)

  • Kim, Byoung-Soo;Lee, Yong-Hun;Lee, Jong-Hyeok
    • Journal of KIISE:Software and Applications
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    • v.34 no.2
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    • pp.112-122
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    • 2007
  • Training a statistical model for semantic role labeling requires a large amount of manually tagged corpus. However. such corpus does not exist for Korean and constructing one from scratch is a very long and tedious job. This paper suggests a modified algorithm of self-training, an unsupervised algorithm, which trains a semantic role labeling model from any raw corpora. For initial training, a small tagged corpus is automatically constructed iron case frames in Sejong Electronic Dictionary. Using the corpus, a probabilistic model is trained incrementally, which achieves 83.00% of accuracy in 4 selected adverbial cases.

Probabilistic Analysis of Drought Characteristics in Pakistan Using a Bivariate Copula Model

  • Jehanzaib, Muhammad;Kim, Ji Eun;Park, Ji Yeon;Kim, Tae-Woong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.151-151
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    • 2019
  • Because drought is a complex and stochastic phenomenon in nature, statistical approaches for drought assessment receive great attention for water resource planning and management. Generally drought characteristics such as severity, duration and intensity are modelled separately. This study aims to develop a relationship between drought characteristics using a bivariate copula model. To achieve the objective, we calculated the Standardized Precipitation Index (SPI) using rainfall data at 6 rain gauge stations for the period of 1961-1999 in Jehlum River Basin, Pakistan, and investigated the drought characteristics. Since there is a significant correlation between drought severity and duration, they are usually modeled using different marginal distributions and joint distribution function. Using exponential distribution for drought severity and log-logistic distribution for drought duration, the Galambos copula was recognized as best copula to model joint distribution of drought severity and duration based on the KS-statistic. Various return periods of drought were calculated to identify time interval of repeated drought events. The result of this study can provide useful information for effective water resource management and shows superiority against univariate drought analysis.

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An advanced technique to predict time-dependent corrosion damage of onshore, offshore, nearshore and ship structures: Part I = generalisation

  • Kim, Do Kyun;Wong, Eileen Wee Chin;Cho, Nak-Kyun
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.12 no.1
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    • pp.657-666
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    • 2020
  • A reliable and cost-effective technique for the development of corrosion damage model is introduced to predict nonlinear time-dependent corrosion wastage of steel structures. A detailed explanation on how to propose a generalised mathematical formulation of the corrosion model is investigated in this paper (Part I), and verification and application of the developed method are covered in the following paper (Part II) by adopting corrosion data of a ship's ballast tank structure. In this study, probabilistic approaches including statistical analysis were applied to select the best fit probability density function (PDF) for the measured corrosion data. The sub-parameters of selected PDF, e.g., the largest extreme value distribution consisting of scale, and shape parameters, can be formulated as a function of time using curve fitting method. The proposed technique to formulate the refined time-dependent corrosion wastage model (TDCWM) will be useful for engineers as it provides an easy and accurate prediction of the 1) starting time of corrosion, 2) remaining life of the structure, and 3) nonlinear corrosion damage amount over time. In addition, the obtained outcome can be utilised for the development of simplified engineering software shown in Appendix B.

Bayesian approach for the accuracy evaluating of the seismic demand estimation of SMRF

  • Ayoub Mehri Dehno;Hasan Aghabarati;Mehdi Mahdavi Adeli
    • Earthquakes and Structures
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    • v.26 no.2
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    • pp.117-130
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    • 2024
  • Probabilistic model of seismic demand is the main tool used for seismic demand estimation, which is a fundamental component of the new performance-based design method. This model seeks to mathematically relate the seismic demand parameter and the ground motion intensity measure. This study is intended to use Bayesian analysis to evaluate the accuracy of the seismic demand estimation of Steel moment resisting frames (SMRFs) through a completely Bayesian method in statistical calculations. In this study, two types of intensity measures (earthquake intensity-related indices such as magnitude and distance and intensity indices related to ground motion and spectral response including peak ground acceleration (PGA) and spectral acceleration (SA)) have been used to form the models. In addition, an extensive database consisting of sixty accelerograms was used for time-series analysis, and the target structures included five SMRFs of three, six, nine, twelve and fifteen stories. The results of this study showed that for low-rise frames, first mode spectral acceleration index is sufficient to accurately estimate demand. However, for high-rise frames, two parameters should be used to increase the accuracy. In addition, adding the product of the square of earthquake magnitude multiplied by distance to the model can significantly increase the accuracy of seismic demand estimation.

Probabilistic modeling of geopolymer concrete using response surface methodology

  • Kathirvel, Parthiban;Kaliyaperumal, Saravana Raja Mohan
    • Computers and Concrete
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    • v.19 no.6
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    • pp.737-744
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    • 2017
  • Geopolymer Concrete is typically proportioned with activator solution leading to moderately high material cost. Such cost can be enduring in high value added applications especially when cost savings can be recognized in terms of reduction in size of the members. Proper material selection and mix proportioning can diminish the material cost. In the present investigation, a total of 27 mixes were arrived considering the mix parameters as liquid-binder ratio, slag content and sodium hydroxide concentration to study the mechanical properties of geopolymer concrete (GPC) mixes such as compressive strength, split tensile strength and flexural strength. The derived statistical Response Surface Methodology is beleaguered to develop cost effective GPC mixes. The estimated responses are not likely to contrast in linear mode with selected variables; a plan was selected to enable the model of any response in a quadratic manner. The results reveals that a fair correlation between the experimental and the predicted strengths.