• 제목/요약/키워드: Random Factor Method

검색결과 322건 처리시간 0.026초

교량응력보정계수 산정방법 개선 (An Improved Method for Determining Response Correction Factor in Bridge Load Rating)

  • 신재인;이상순;이상달
    • 한국콘크리트학회:학술대회논문집
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    • 한국콘크리트학회 2000년도 가을 학술발표회 논문집(II)
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    • pp.1273-1278
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    • 2000
  • Bridge load rating calculations provide a basis for determining the safe load capacity of bridge. Load rating requires engineering judgement in determining a rating value that is applicable to maintaining the safe use of the bridge and arriving at posting and permit decisions. Load testing is an effective means in calculating the rating value of bridge. In Korea, load carrying capacity of bridge is modified by stress modification factor that is determined from comparisons of measured values and analysis results The stress modification factor may be corrupted by vehicle location error that is defined as the gap of test vehicle location between load testing and analysis. In this study, the effects of vehicle location error to structural response and stress modification factor are investigated, and a new method for evaluating stress modification factor is proposed. The random data analysis shows that the proposed method is less sensitive to vehicle location error than the present method.

Reliability and risk assessment for rainfall-induced slope failure in spatially variable soils

  • Zhao, Liuyuan;Huang, Yu;Xiong, Min;Ye, Guanbao
    • Geomechanics and Engineering
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    • 제22권3호
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    • pp.207-217
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    • 2020
  • Slope reliability analysis and risk assessment for spatially variable soils under rainfall infiltration are important subjects but they have not been well addressed. This lack of study may in part be due to the multiple and diverse evaluation indexes and the low computational efficiency of Monte-Carlo simulations. To remedy this, this paper proposes a highly efficient computational method for investigating random field problems for slopes. First, the probability density evolution method (PDEM) is introduced. This method has high computational efficiency and does not need the tens of thousands of numerical simulation samples required by other methods. Second, the influence of rainfall on slope reliability is investigated, where the reliability is calculated from based on the safety factor curves during the rainfall. Finally, the uncertainty of the sliding mass for the slope random field problem is analyzed. Slope failure consequences are considered to be directly correlated with the sliding mass. Calculations showed that the mass that slides is smaller than the potential sliding mass (shallow surface sliding in rainfall). Sliding mass-based risk assessment is both needed and feasible for engineered slope design. The efficient PDEM is recommended for problems requiring lengthy calculations such as random field problems coupled with rainfall infiltration.

Autoregressive Cholesky Factor Modeling for Marginalized Random Effects Models

  • Lee, Keunbaik;Sung, Sunah
    • Communications for Statistical Applications and Methods
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    • 제21권2호
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    • pp.169-181
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    • 2014
  • Marginalized random effects models (MREM) are commonly used to analyze longitudinal categorical data when the population-averaged effects is of interest. In these models, random effects are used to explain both subject and time variations. The estimation of the random effects covariance matrix is not simple in MREM because of the high dimension and the positive definiteness. A relatively simple structure for the correlation is assumed such as a homogeneous AR(1) structure; however, it is too strong of an assumption. In consequence, the estimates of the fixed effects can be biased. To avoid this problem, we introduce one approach to explain a heterogenous random effects covariance matrix using a modified Cholesky decomposition. The approach results in parameters that can be easily modeled without concern that the resulting estimator will not be positive definite. The interpretation of the parameters is sensible. We analyze metabolic syndrome data from a Korean Genomic Epidemiology Study using this method.

평면 FRAME 구조물의 확률유한요소 해석 (Probabilistic Finite Element Analysis of Plane Frame)

  • 양영순;김지호
    • 전산구조공학
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    • 제2권4호
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    • pp.89-98
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    • 1989
  • 구조해석에 사용되는 변수들이 갖고 있는 통계적 특성을 고려하기 위해 기존의 방법에서는 경험에 입각한 안전계수를 사용하여, 변수가 갖고 있는 불확실성을 정성적으로 취급하여 구조물의 안전성을 점검하여 왔다. 그러나, 최근 확률이론에 입각한 신뢰성이론을 적용하여 구조물의 안전성을 보다 정량적으로 파악하여 충분한 경험과 실적이 부족한 새로운 형태의 구조물의 안전성 점검에도 활용하려는 시도가 많이 이루어지고 있다. 이러한 추세에 따라, 본 연구에서는 기존의 유한요소법에 확률론적 수법을 가미한 확률 유한요소법을 개발하여, 구조해석에 사용되는 변수들이 갖고 있는 불확실량들이 구조해석의 최종결과에 어떤 영향을 미치는가를 확률적으로 처리하여, 구조물의 안전성을 보다 합리적으로 평가하도록 하였다.

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Partial safety factors for retaining walls and slopes: A reliability based approach

  • GuhaRay, Anasua;Baidya, Dilip Kumar
    • Geomechanics and Engineering
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    • 제6권2호
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    • pp.99-115
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    • 2014
  • Uncertainties in design variables and design equations have a significant impact on the safety of geotechnical structures like retaining walls and slopes. This paper presents a possible framework for obtaining the partial safety factors based on reliability approach for different random variables affecting the stability of a reinforced concrete cantilever retaining wall and a slope under static loading conditions. Reliability analysis is carried out by Mean First Order Second Moment Method, Point Estimate Method, Monte Carlo Simulation and Response Surface Methodology. A target reliability index ${\beta}$ = 3 is set and partial safety factors for each random variable are calculated based on different coefficient of variations of the random variables. The study shows that although deterministic analysis reveals a safety factor greater than 1.5 which is considered to be safe in conventional approach, reliability analysis indicates quite high failure probability due to variation of soil properties. The results also reveal that a higher factor of safety is required for internal friction angle ${\varphi}$, while almost negligible values of safety factors are required for soil unit weight ${\gamma}$ in case of cantilever retaining wall and soil unit weight ${\gamma}$ and cohesion c in case of slope. Importance of partial safety factors is shown by analyzing two simple geotechnical structures. However, it can be applied for any complex system to achieve economization.

랜덤하중에서의 균열전파속도 추정법에 관한 연구 (A Prediction of Crack Propagation Rate under Random Loading)

  • 표동근;안태환
    • 한국해양공학회지
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    • 제8권2호
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    • pp.115-123
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    • 1994
  • Under variable amplitude loading conditions, retardation or accelerated condition of fatigue crack growth occurs with every cycle, Because fatigue crack growth behavior varied depend on load time history. The modeling of stress amplitude with storm loading acted to ships and offshore structures applied this paper. The crack closure behavior examine by recording the variation in load-strain relationship. By taking process mentioned above, fatigue crack growth rate, crack length, stress intensity factor, and crack closure stress intensity factor were obtained from the stress cycles of each type of storm ; A(6m), B(7m), C(8m), D(9m), E(11m) and F(15m) which was wave height. It showed that the good agreement with between the experiment results and simulation of storm loads. So this estimated method of crack propagtion rate gives a good criterion for the safe design of vessels and marine structure.

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일정 응력확대계수 제어하의 피로균열전파수명 분포의 파라메터 특성 (Characteristics of Parameters for the Distribution of fatigue Crack Growth Lives wider Constant Stress Intensity factor Control)

  • 김선진
    • 한국해양공학회지
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    • 제17권2호
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    • pp.54-59
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    • 2003
  • The characteristics of the parameters for the probability distribution of fatigue crack growth life, using the non-Gaussian random process simulation method is investigated. In this paper, the material resistance to fatigue crack growth is treated as a spatial random process, which varies randomly on the crack surface. Using the previous experimental data, the crack length equals the number of cycle curves that are simulated. The results are obtained for constant stress intensity factor range conditions with stress ratios of R=0.2, three specimen thickness of 6, 12 and 18mm, and the four stress intensity level. The probability distribution function of fatigue crack growth life seems to follow the 3-parameter Wiubull,, showing a slight dependence on specimen thickness and stress intensity level. The shape parameter, $\alpha$, does not show the dependency of thickness and stress intensity level, but the scale parameter, $\beta$, and location parameter, ${\gamma}$, are decreased by increasing the specimen thickness and stress intensity level. The slope for the stress intensity level is larger than the specimen thickness.

일정 응력확대계수 제어하의 피로균열전파수명 분포의 파라메터 특성에 관하여 (Characteristics of Parameters for the Distribution of Fatigue Crack Growth Lives under Constant Stress Intensity Factor Control)

  • 김선진;김영식;정현철
    • 한국해양공학회:학술대회논문집
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    • 한국해양공학회 2002년도 추계학술대회 논문집
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    • pp.301-306
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    • 2002
  • The characteristics of parameters for the probability distribution of fatigue crack growth lives by the non-Gaussian random process simulation method is investigated. In this paper, the material resistance to fatigue crack growth is treated as a spatial random process, which varies randomly on the crack surface. Using the previous experimental data, the crack length - the number of cycles curves are simulated. The results are obtained for constant stress intensity factor range conditions with stress ratio of R=0.2, three specimen thickness of 6, 12 and 18mm, and the four stress intensity level. The probability distribution function of fatigue crack growth lives seems to follow the 3-parameter Wiubull and shows a slight dependence on specimen thickness and stress intensity level. The shape parameter, ${\alpha}$, does not show the dependency of thickness and stress intensity level, but the scale parameter, ${\beta}$, and location parameter, ${\upsilon}$, are decreased by increasing the specimen thickness and stress intensity level. The slope for the stress intensity level is larger than the specimen thickness.

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머신러닝 기반 CFS(Correlation-based Feature Selection)기법과 Random Forest모델을 활용한 BMI(Benthic Macroinvertebrate Index) 예측에 관한 연구 (A Study on the prediction of BMI(Benthic Macroinvertebrate Index) using Machine Learning Based CFS(Correlation-based Feature Selection) and Random Forest Model)

  • 고우석;윤춘경;이한필;황순진;이상우
    • 한국물환경학회지
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    • 제35권5호
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    • pp.425-431
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    • 2019
  • Recently, people have been attracting attention to the good quality of water resources as well as water welfare. to improve the quality of life. This study is a papers on the prediction of benthic macroinvertebrate index (BMI), which is a aquatic ecological health, using the machine learning based CFS (Correlation-based Feature Selection) method and the random forest model to compare the measured and predicted values of the BMI. The data collected from the Han River's branch for 10 years are extracted and utilized in 1312 data. Through the utilized data, Pearson correlation analysis showed a lack of correlation between single factor and BMI. The CFS method for multiple regression analysis was introduced. This study calculated 10 factors(water temperature, DO, electrical conductivity, turbidity, BOD, $NH_3-N$, T-N, $PO_4-P$, T-P, Average flow rate) that are considered to be related to the BMI. The random forest model was used based on the ten factors. In order to prove the validity of the model, $R^2$, %Difference, NSE (Nash-Sutcliffe Efficiency) and RMSE (Root Mean Square Error) were used. Each factor was 0.9438, -0.997, and 0,992, and accuracy rate was 71.6% level. As a result, These results can suggest the future direction of water resource management and Pre-review function for water ecological prediction.

OFDM 시스템에서 PAPR 처감을 위한 SPW 방식의 설계와 성능 분석 (Design and Performance Analysis of the SPW Method for PAPR Reduction in OFDM System)

  • 이재은;유흥균;정영호;함영권
    • 한국전자파학회논문지
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    • 제14권7호
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    • pp.677-684
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    • 2003
  • OFDM에서 PAPR(peak-to-average power ratio) 저감에 효과적인 SPW(subblock phase weighting) 방법을 연구하였다. 이 방법은 OFDM 신호 블록을 여러 개의 하부 블록으로 나누고 하부 블록별로 위상을 적절히 조절하여 peak power를 낮추는 것이다. SPW는 하나의 IFFT로 구현할 수 있어 시스템의 복잡도를 낮출 수 있다. 인접, 인터리브드, 랜덤 subblock분할 방법을 적용하여 PAPR저감 성능을 분석하였다 랜덤 subblock분할 방법이 가장 우수한 PAPR 저감성능을 보인다. SPW에서 하부 블록의 수가 증가할수록 효과적인 PAPR 저감성능을 보이지만 반복 탐색 횟수가 증가하여 처리 시간이 길어진다. 본 논문에서는 새로이 상보 시퀀스 특성의 weighting factor조합을 임계치 기법과 혼합하여 사용하므로 처리시간 문제를 해결한다. weighting factor에 대 한 부가 정보를 fed forward 형태로 전송하므로 데이터를 복원할 수 있으며, BER 성능을 분석하였다.