• 제목/요약/키워드: Weibull Probabilistic Distribution

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몬테카를로 시뮬레이션을 이용한 증기 터빈블레이드재의 확률론적 해석 (A Stochastic Analysis in Steam Turbine Blade Steel Using Monte Carlo Simulation)

  • 김철수;정화영;강명수;김정규
    • 대한기계학회논문집A
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    • 제26권11호
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    • pp.2421-2428
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    • 2002
  • In this study, the failure probability of the degraded LP turbine blade steel was performed using the Monte Carlo simulation to apply variation of applied stress and strength. For this purpose, applied stress under the service condition of steady state was obtained by theoretical stress analysis and the maximum Von-Mises stress was 219MPa. The fatigue strength under rotating-bending load was evaluated by the staircase method. Furthermore, 3-parameter Weibull distribution was found to be most appropriate among assumed distributions when the probabilistic distributions of tensile and fatigue strength were determined by the proposed analysis. The failure probability with various loading conditions was derived from the strength-stress interference model and the characteristic factor of safety was also estimated.

일 강우량의 모의 발생을 통한 갈수유량 계열의 산정 및 빈도분석 (Low Flow Frequency Analysis of Steamflows Simulated from the Stochastically Generated Daily Rainfal Series)

  • 김병식;강경석;서병하
    • 한국수자원학회논문집
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    • 제32권3호
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    • pp.265-279
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    • 1999
  • 본 연구에서는, Markov 연쇄 모형에 의해 산정된 모의 일 강우량을 일 유출모형인 Tand 모형에 입력시켜 모의 일유출량을 산정함으로써 저수유량계열을 확장하는 방법을 개발하였다. 또한, 모의된 일 유량계열로부터 지속기간별 연 최저치 계열을 작성하였으며, 지속기간별 연 최저치계열에 대한 빈도분석을 시행하였다. 분석에 사용된 분포형은 Lognormal-2, Lognormal-3, Gamma-2, Gamma-3, LogGamma-3, Gumbel-2, Weibull-2 분포이었으며, 모수추정은 모멘트법과 최우도법을 사용하였다. Kolmogorov - Sminorv 검정방법으로 지속기간별 연 최저치 계열에 적합한 확률분포형을 결정하고, 용담댐 지점을 대상으로 하여 지속기간별 갈수 빈도곡선을 산정하였다. 본 연구에서 제안된 방법을 적용하면 과거 저수 유량계열의 통계적 특성을 잘 나타내는 일 유량의 모의가 가능 하여, 갈수유량계열 자료가 빈곤한 유역에서 확률 갈수량을 추정하는데 유용하리라고 판단된다.

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어린이용품 노출평가 연구에서의 결정론적 및 확률론적 방법론 사용실태 분석 및 고찰 (Comparison of Deterministic and Probabilistic Approaches through Cases of Exposure Assessment of Child Products)

  • 장보윤;정다인;이헌주
    • 한국환경보건학회지
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    • 제43권3호
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    • pp.223-232
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    • 2017
  • Objectives: In response to increased interest in the safety of children's products, a risk management system is being prepared through exposure assessment of hazardous chemicals. To estimate exposure levels, risk assessors are using deterministic and probabilistic approaches to statistical methodology and a commercialized Monte Carlo simulation based on tools (MCTool) to efficiently support calculation of the probability density functions. This study was conducted to analyze and discuss the usage patterns and problems associated with the results of these two approaches and MCTools used in the case of probabilistic approaches by reviewing research reports related to exposure assessment for children's products. Methods: We collected six research reports on exposure and risk assessment of children's products and summarized the deterministic results and corresponding underlying distributions for exposure dose and concentration results estimated through deterministic and probabilistic approaches. We focused on mechanisms and differences in the MCTools used for decision making with probabilistic distributions to validate the simulation adequacy in detail. Results: The estimation results of exposure dose and concentration from the deterministic approaches were 0.19-3.98 times higher than the results from the probabilistic approach. For the probabilistic approach, the use of lognormal, Student's T, and Weibull distributions had the highest frequency as underlying distributions of the input parameters. However, we could not examine the reasons for the selection of each distribution because of the absence of test-statistics. In addition, there were some cases estimating the discrete probability distribution model as the underlying distribution for continuous variables, such as weight. To find the cause of abnormal simulations, we applied two MCTools used for all reports and described the improper usage routes of MCTools. Conclusions: For transparent and realistic exposure assessment, it is necessary to 1) establish standardized guidelines for the proper use of the two statistical approaches, including notes by MCTool and 2) consider the development of a new software tool with proper configurations and features specialized for risk assessment. Such guidelines and software will make exposure assessment more user-friendly, consistent, and rapid in the future.

원공을 가진 CFRP 복합재료의 피로누적손상 및 피로수명에 대한 확률적 해석 (A Probabilistic Analysis for Fatigue Cumulative Damage and Fatigue Life in CFRP Composites Containing a Circular Hole)

  • 김정규;김도식
    • 대한기계학회논문집
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    • 제19권8호
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    • pp.1915-1926
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    • 1995
  • The Fatigue characteristics of 8-harness satin woven CFRP composites with a circular hole are experimentally investigated under constant amplitude tension-tension loading. It is found in this study that the fatigue damage accumulation behavior is very random and history-independent, and the fatigue cumulative damage is linearly related with the mean number of cycles to a specified damage state. From these results, it is known that the fatigue characteristics of CFRP composites satisfy the basic assumptions of Markov chain theory and the parameter of Markov chain model can be determined only by mean and variance of fatigue lives. The predicted distribution of the fatigue cumulative damage using Markov chain model shows a good agreement with the test results. For the fatigue life distribution, Markov chain model makes similar accuracy to 2-parameter Weibull distribution function.

확률적 방법에 의한 크리프 균열성장 계수의 분포 추정 (Estimation for the Distribution of Creep Crack Growth Coefficients by Probabilistic Assessment)

  • 이상호;윤기봉;최병학;민두식;안종석;이길재;김선화
    • 대한금속재료학회지
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    • 제48권9호
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    • pp.791-797
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    • 2010
  • The creep crack growth rate (da/dt) of the Cr-Mo steels tested by pre-crack and the voltage (or resistance) variables were related into fracture parameter (Ct), crack growth coefficient (H), and an exponent (q) in the parts of Base, weld and HAZ. The fracture parameter (Ct) has various variables relating to the specimen and crack shape, applied stress, and creep strain curve. The H and q was inferred by OLS regression (ordinary least square method), and the H values were solved in statistics and probability assessment, which were attained fromPDF's distributions (probability density function). The HAZ part has the highest value of q by OLS regression and the widest distribution of H by PDF of WEIBULL, which means that the crack sensitivity of HAZ should be cautioned against the creep crack growth and failure.

Analysis and probabilistic modeling of wind characteristics of an arch bridge using structural health monitoring data during typhoons

  • Ye, X.W.;Xi, P.S.;Su, Y.H.;Chen, B.
    • Structural Engineering and Mechanics
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    • 제63권6호
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    • pp.809-824
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    • 2017
  • The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

Quantitative microbial risk assessment of Campylobacter jejuni in jerky in Korea

  • Ha, Jimyeong;Lee, Heeyoung;Kim, Sejeong;Lee, Jeeyeon;Lee, Soomin;Choi, Yukyung;Oh, Hyemin;Yoon, Yohan
    • Asian-Australasian Journal of Animal Sciences
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    • 제32권2호
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    • pp.274-281
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    • 2019
  • Objective: The objective of this study was to estimate the risk of Campylobacter jejuni (C. jejuni) infection from various jerky products in Korea. Methods: For the exposure assessment, the prevalence and predictive models of C. jejuni in the jerky and the temperature and time of the distribution and storage were investigated. In addition, the consumption amounts and frequencies of the products were also investigated. The data for C. jejuni for the prevalence, distribution temperature, distribution time, consumption amount, and consumption frequency were fitted with the @RISK fitting program to obtain appropriate probabilistic distributions. Subsequently, the dose-response models for Campylobacter were researched in the literature. Eventually, the distributions, predictive model, and dose-response model were used to make a simulation model with @RISK to estimate the risk of C. jejuni foodborne illness from the intake of jerky. Results: Among 275 jerky samples, there were no C. jejuni positive samples, and thus, the initial contamination level was statistically predicted with the RiskUniform distribution [RiskUniform (-2, 0.48)]. To describe the changes in the C. jejuni cell counts during distribution and storage, the developed predictive models with the Weibull model (primary model) and polynomial model (secondary model) were utilized. The appropriate probabilistic distribution was the BetaGeneral distribution, and it showed that the average jerky consumption was 51.83 g/d with a frequency of 0.61%. The developed simulation model from this data series and the dose-response model (Beta Poisson model) showed that the risk of C. jejuni foodborne illness per day per person from jerky consumption was $1.56{\times}10^{-12}$. Conclusion: This result suggests that the risk of C. jejuni in jerky could be considered low in Korea.

열충격이 작용하는 취성구조의 신뢰성 평가 (Reliability evaluation of brittle structures under thermal shocks)

  • 이치우;장건익;김종태
    • 한국해양공학회지
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    • 제12권1호
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    • pp.58-64
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    • 1998
  • An analysis method for the reliability of ceramic structures subjected to thermal shocks is presented. Flaws with the size of given probability distribution function are assumed to be distributed at random with a certain density per unit volume in the structures. Criterions for crack instability are derived for brittle solids under general thermal stresses. A probabilistic failure model is presented to study the probability of crack instability for brittle solids containing cracks with uncertain size. The reliabilities of brittle structures are evaluated based on the weakest-link hypothesis, which states that a structure fails when the cracks in any differential volume become unstable. A numerical example is given to demonstrate the application of the proposed method.

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열충격이 작용하는 세라믹구조의 신뢰성 평가 (Reliability Evaluation of Ceramic Structures Under Thermal Shocks)

  • 김종태;심확섭;장건익;이치우;이환우
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1996년도 추계학술대회 논문집
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    • pp.954-958
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    • 1996
  • An analysis method for the reliability of ceramic structures subjected to thermal shocks is presented, Flaws with the size of given probability distribution function are assumed to be distributed at random with a certain density per unit volume in the structures. Criterions for crack instability are derived for brittle solids under general thermal stresses. A probabilistic failure model is presented to study the probability of crack instability for blittle solids containing cracks with uncertain crack size. The reliabilities of brittle structures are evaluated based on the weakest-link hypothesis, which states that a structure fails when the cracks in any differential volume become unstable. A numerical example is given to demonstrate the application of the proposed method.

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Parametric survival model based on the Lévy distribution

  • Valencia-Orozco, Andrea;Tovar-Cuevas, Jose R.
    • Communications for Statistical Applications and Methods
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    • 제26권5호
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    • pp.445-461
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    • 2019
  • It is possible that data are not always fitted with sufficient precision by the existing distributions; therefore this article presents a methodology that enables the use of families of asymmetric distributions as alternative probabilistic models for survival analysis, with censorship on the right, different from those usually studied (the Exponential, Gamma, Weibull, and Lognormal distributions). We use a more flexible parametric model in terms of density behavior, assuming that data can be fit by a distribution of stable distribution families considered unconventional in the analyses of survival data that are appropriate when extreme values occur, with small probabilities that should not be ignored. In the methodology, the determination of the analytical expression of the risk function h(t) of the $L{\acute{e}}vy$ distribution is included, as it is not usually reported in the literature. A simulation was conducted to evaluate the performance of the candidate distribution when modeling survival times, including the estimation of parameters via the maximum likelihood method, survival function ${\hat{S}}$(t) and Kaplan-Meier estimator. The obtained estimates did not exhibit significant changes for different sample sizes and censorship fractions in the sample. To illustrate the usefulness of the proposed methodology, an application with real data, regarding the survival times of patients with colon cancer, was considered.