• Title/Summary/Keyword: 확률론적 접근

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Suggestions for Enhancing Sampling-Based Approach of Seismic Probabilistic Risk Assessment (샘플링기반 지진 확률론적 리스크평가 접근법 개선을 위한 제언)

  • Kwag, Shinyoung;Eem, Seunghyun;Choi, Eujeong;Ha, Jeong Gon;Hahm, Daegi
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.2
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    • pp.77-84
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    • 2021
  • A sampling-based approach was devised as a nuclear seismic probabilistic risk assessment (SPRA) method to account for the partially correlated relationships between components. However, since this method is based on sampling, there is a limitation that a large number of samples must be extracted to estimate the results accurately. Thus, in this study, we suggest an effective approach to improve the existing sampling method. The main features of this approach are as follows. In place of the existing Monte Carlo sampling (MCS) approach, the Latin hypercube sampling (LHS) method that enables effective sampling in multiple dimensions is introduced to the SPRA method. In addition, the degree of segmentation of the seismic intensity is determined with respect to the final seismic risk result. By applying the suggested approach to an actual nuclear power plant as an example, the accuracy of the results were observed to be almost similar to those of the existing method, but the efficiency was increased by a factor of two in terms of the total number of samples extracted. In addition, it was confirmed that the LHS-based method improves the accuracy of the solution in a small sampling region.

Durability Prediction for Concrete Structures Exposed to Chloride Attack Using a Bayesian Approach (베이지안 기법을 이용한 염해 콘크리트구조물의 내구성 예측)

  • Jung, Hyun-Jun;Zi, Goang-Seup;Kong, Jung-Sik;Kang, Jin-Gu
    • Journal of the Korea Concrete Institute
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    • v.20 no.1
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    • pp.77-88
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    • 2008
  • This paper provides a new approach for predicting the corrosion resistivity of reinforced concrete structures exposed to chloride attack. In this method, the prediction can be updated successively by a Bayesian theory when additional data are available. The stochastic properties of model parameters are explicitly taken into account into the model. To simplify the procedure of the model, the probability of the durability limit is determined from the samples obtained from the Latin hypercube sampling technique. The new method may be very useful in designing important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored.

기혼여성의 자녀출산계획에 대한 공간효과 분석

  • Sin, In-Cheol
    • Korea journal of population studies
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    • v.32 no.2
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    • pp.59-85
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    • 2009
  • 본 연구는 최근 인구학에서 공간적 접근을 시도하는 논의들이 활발해지는 경향과 함께 지역 적합적 저출산 대응정책의 필요성의 대두라는 정책적 수요에 부합하고자 자녀출산계획에 있어 지역의 공간적 효과가 미치는 효과를 분석하였다. 또한, 기혼여성의 연령, 출산한 자녀의 수가 자녀를 출산할 계획을 가질 확률에 대한 비선형적 효과를 실증적으로 분석하였다. 다층모형과 같이 최근 지역연구에서 이용되고 있는 실증분석방법들의 한계점을 살펴보고, 그 대안으로 Geo-Additive Model을 적용하였다. 동 방법론은 한 모형 내에서 공간의 구조적 효과와 비구조적 효과, 연속형 변인의 비선형효과 등을 동시에 추정할 수 있다. 이를 위한 분석자료로 통계청의 2005년도 인구주택총조사의 마이크로데이터 중 2% B형 자료를 이용하였다. 분석결과 기혼여성이 자녀를 출산할 계획을 가질 확률에 기혼여성의 연령과 출산한 자녀의 수는 비선형적 효과를 주었으며, 특히 각 개인들은 현재의 출산 상태에서 자녀 한명을 추가로 출산하는 것이 동일한 부담으로 작용하지 않음을 알 수 있었다. 이를 통해 기혼여성들의 첫출산 시점이 결혼연령에 따라 차이가 있고 결혼코호트에 따라 다르더라도 첫출산 자체가 여전히 보편적인 현상이라는 가정을 받아들인다면, 출산율 제고를 위한 정책의 대상은 첫째아를 이미 출산한 여성들이 되어야 할 것으로 보인다. 또한, 자녀를 출산할 계획을 가질 확률에 지역의 구조적 공간효과가 유의미한 영향을 주는 것으로 분석되었다. 지역별 합계출산율의 공간 자기상관분석 결과와 비교해 본 결과 출산계획의 구조적 공간효과가 양의 효과를 미치는 지역에서는 실제 출산행위인 합계출산율도 높지만, 구조적 공간효과가 부적인 효과를 가지고 있는 지역에서는 합계출산율도 낮게 나타남을 알 수 있었다. 따라서 각 지방자치단체에서는 지자체들의 정책수요나 자원 및 재정의 부담능력 등 지역별 차이를 고려하지 않은 일률적인 정책의 추진을 지양하고, 지역 특수성을 고려하여 지역에 적합한 출산정책을 추진해야 할 것이다.

Investigation on the Temperature Characteristics of CWR for the Climate Change (기후변화에 대비한 장대레일 온도특성 연구)

  • Choi, Jin-Yu;Lee, Gyu-Sei;Bae, Hyun-Ung;Park, Beom-Ho;Lim, Nam-Hyoung
    • Journal of the Korean Society for Railway
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    • v.13 no.2
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    • pp.179-185
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    • 2010
  • In order to secure safety for the buckling and fracture of continuous welded rail and improve the efficiency of maintenance work, it is very important that grasp the characteristics of rail temperature. Recently, the maximum air temperature in summer season rises gradually and the minimum air temperature in winter season is decreasing gradually due to the climate change. Therefore, these phenomenon influences in the change amount of yearly rail temperature and can cause change of laying and maintenance temperature. In this study, actual measurement of rail temperature including climatic factors is carried out by constructing the temperature and climate measurement system as realistic as possible. Through the intensive investigation of actual data, it is founded that the existing prediction formulas for rail temperature may be used only in certain climatic conditions (certain combination of climatic factors). It may be more reasonable that the rail temperature considering actual climatic factors in site is predicted on probabilistic approach.

Probabilistic Approach for Predicting Degradation Characteristics of Corrosion Fatigue Crack (환경피로균열 열화특성 예측을 위한 확률론적 접근)

  • Lee, Taehyun;Yoon, Jae Young;Ryu, KyungHa;Park, Jong Won
    • Journal of Applied Reliability
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    • v.18 no.3
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    • pp.271-279
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    • 2018
  • Purpose: Probabilistic safety analysis was performed to enhance the safety and reliability of nuclear power plants because traditional deterministic approach has limitations in predicting the risk of failure by crack growth. The study introduces a probabilistic approach to establish a basis for probabilistic safety assessment of passive components. Methods: For probabilistic modeling of fatigue crack growth rate (FCGR), various FCGR tests were performed either under constant load amplitude or constant ${\Delta}K$ conditions by using heat treated X-750 at low temperature with adequate cathodic polarization. Bayesian inference was employed to update uncertainties of the FCGR model using additional information obtained from constant ${\Delta}K$ tests. Results: Four steps of Bayesian parameter updating were performed using constant ${\Delta}K$ test results. The standard deviation of the final posterior distribution was decreased by a factor of 10 comparing with that of the prior distribution. Conclusion: The method for developing a probabilistic crack growth model has been designed and demonstrated, in the paper. Alloy X-750 has been used for corrosion fatigue crack growth experiments and modeling. The uncertainties of parameters in the FCGR model were successfully reduced using the Bayesian inference whenever the updating was performed.

Random Vibration Analysis of Nonlinear Stochastic System under Earthquake Using Statistical Method (지진하중을 받는 비선헝 추계적 시스템의 불규칙진동해석)

  • Moon, Byung-Young;Kang, Gyung-Ju;Kang, Beom-Soo
    • Journal of the Earthquake Engineering Society of Korea
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    • v.5 no.6
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    • pp.55-64
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    • 2001
  • Industrial machines are sometimes exposed to the danger of earthquake. In the design of a mechanical system, this factor should be accounted for from the viewpoint of reliability to analyze a complex nonlinear structure system under random excitation is proposed. First, the actual random excitation, such as earthquake, is approximated to the corresponding Gaussian process for the statistical analysis. The modal equations of overall system are expanded sequentially. Then, the perturbed equations are synthesized into the overall system and solved in probabilistic way. Several statistical properties of a random process that are of interest in random vibration are evaluated in each substructure. Comparing with the results of the numerical simulation proved the efficiency of the proposed method.

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A Study on the Neural Networks for Korean Phoneme Recognition (한국어 음소 인식을 위한 신경회로망에 관한 연구)

  • Choi, Young-Bae;Yang, Jin-Woo;Lee, Hyung-Jun;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.13 no.1
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    • pp.5-13
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    • 1994
  • This paper presents a study on Neural Networks for Phoneme Recognition and performs the Phoneme Recognition using TDNN (Time Delay Neural Network). Also, this paper proposes training algorithm for speech recognition using neural nets that is a proper to large scale TDNN. Because Phoneme Recognition is indispensable for continuous speech recognition, this paper uses TDNN to get accurate recognition result of phonemes. And this paper proposes new training algorithm that can converge TDNN to an optimal state regardless of the number of phonemes to be recognized. The recognition experiment was performed with new training algorithm for TDNN that combines backpropagation and Cauchy algorithm using stochastic approach. The results of the recognition experiment for three phoneme classes for two speakers show the recognition rates of $98.1\%$. And this paper yielded that the proposed algorithm is an efficient method for higher performance recognition and more reduced convergence time than TDNN.

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Drought Frequency Analysis Using Hidden Markov Chain Model and Bivariate Copula Function (Hidden Markov Chain 모형과 이변량 코플라함수를 이용한 가뭄빈도분석)

  • Chun, Si-Young;Kim, Yong-Tak;Kwon, Hyun-Han
    • Journal of Korea Water Resources Association
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    • v.48 no.12
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    • pp.969-979
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    • 2015
  • This study applied a probabilistic-based hidden Markov model (HMM) to better characterize drought patterns. In addition, a copula-based bivariate drought frequency analysis was employed to further investigate return periods of the current drought condition in year 2015. The obtained results revealed that western Kangwon area was generally more vulnerable to drought risk than eastern Kangwon area using the 40-year data. Imjin-river watershed including Cheorwon area was the most vulnerable area in terms of severe drought events. Four stations in Han-river watershed showed a joint return period exceeding 1,000 years associated with the drought duration and severity in 2014-2015. Especially, current drought status in Northern Han-river and Imjin-river watershed is most severe drought exceeding 100-year return period.

Bayesian Reliability Analysis Using Kriging Dimension Reduction Method(KDRM) (크리깅 기반 차원감소법을 이용한 베이지안 신뢰도 해석)

  • An, Da-Un;Choi, Joo-Ho;Won, Jun-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.21 no.3
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    • pp.275-280
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    • 2008
  • A technique for reliability-based design optimization(RBDO) is developed based on the Bayesian approach, which can deal with the epistemic uncertainty arising due to the limited number of data. Until recently, the conventional REDO was implemented mostly by assuming the uncertainty as aleatory which means the statistical properties are completely known. In practice, however, this is not the case due to the insufficient data for estimating the statistical information, which makes the existing RBDO methods less useful. In this study, a Bayesian reliability is introduced to take account of the epistemic uncertainty, which is defined as the lower confidence bound of the probability distribution of the original reliability. In this case, the Bayesian reliability requires double loop of the conventional reliability analyses, which can be computationally expensive. Kriging based dimension reduction method(KDRM), which is a new efficient tool for the reliability analysis, is employed to this end. The proposed method is illustrated using a couple of numerical examples.

An Approach to Risk Assessment of City Gas Pipeline (도시가스 배관의 위험평가 방법론 제시)

  • Park Kyo-Shik;Lee Jin-Han;Jo Young-Do;Park Jin-Hee
    • Journal of the Korean Institute of Gas
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    • v.7 no.1 s.18
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    • pp.33-40
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    • 2003
  • In this work, a novel approach was introduced to assess cost of loss resulting from risk as well as to help deciding inspection period through quantifying risk. In order to quantifying risk of city gas pipeline, frequency and consequence analysis were required. The main causes of city gas accident were analyzed to be digging, external corrosion, ground movement, and equipment failure. Tools to evaluate frequency of each cause was also suggested. Among city gas accidents, fire damage is the dominant one and mainly discussed; fatality, burning injury, and damage to building were estimated using the consequence model suggested. By combining frequency and consequence analysis, evaluating cost of risk management together with calculating example. This work could be applicable for city gas companies to plan how to manage risk most effectively.

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