• Title/Summary/Keyword: mixed Weibull distribution

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Non-Gaussian feature of fluctuating wind pressures on rectangular high-rise buildings with different side ratios

  • Jia-hui Yuan;Shui-fu Chen;Yi Liu
    • Wind and Structures
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    • v.37 no.3
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    • pp.211-227
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    • 2023
  • To investigate the non-Gaussian feature of fluctuating wind pressures on rectangular high-rise buildings, wind tunnel tests were conducted on scale models with side ratios ranging from 1/9~9 in an open exposure for various wind directions. The high-order statistical moments, time histories, probability density distributions, and peak factors of pressure fluctuations are analyzed. The mixed normal-Weibull distribution, Gumbel-Weibull distribution, and lognormal-Weibull distribution are adopted to fit the probability density distribution of different non-Gaussian wind pressures. Zones of Gaussian and non-Gaussian are classified for rectangular buildings with various side ratios. The results indicate that on the side wall, the non-Gaussian wind pressures are related to the distance from the leading edge. Apart from the non-Gaussianity in the separated flow regions noted by some literature, wind pressures behind the area where reattachment happens present non-Gaussian nature as well. There is a new probability density distribution type of non-Gaussian wind pressure which has both long positive and negative tail found behind the reattachment regions. The correlation coefficient of wind pressures is proved to reflect the non-Gaussianity and a new method to estimate the mean reattachment length of rectangular high-rise building side wall is proposed by evaluating the correlation coefficient. For rectangular high-rise buildings, the mean reattachment length calculated by the correlation coefficient method along the height changes in a parabolic shape. Distributions of Gaussian and non-Gaussian wind pressures vary with side ratios. It is inappropriate to estimate the extreme loads of wind pressures using a fixed peak factor. The trend of the peak factor with side ratios on different walls is given.

Statistical analysis and probabilistic modeling of WIM monitoring data of an instrumented arch bridge

  • Ye, X.W.;Su, Y.H.;Xi, P.S.;Chen, B.;Han, J.P.
    • Smart Structures and Systems
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    • v.17 no.6
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    • pp.1087-1105
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    • 2016
  • Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

Optimal Burn-In under Waranty

  • Kim, Kui-Nam;Lee, Kwang-Ho
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.719-728
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    • 1999
  • This paper discusses an optimal burn-in procedure to minimize total costs based on the assumption that the failure rate pattern follows a bimodal mixed Weibull distribution. The procedure will consider warranty period as a factor of the total expected burn-in cost. A cost model is formulated to find the optimal burn-in time that minimizes the expected burn-in cost. Conditional reliability for warranty period will be discussed. An illustrative example is included to show how to use the cost model in prctice.

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Statistical frequency analysis of snow depth using mixed distributions (혼합분포함수를 적용한 최심신적설량에 대한 수문통계학적 빈도분석)

  • Park, Kyung Woon;Kim, Dongwook;Shin, Ji Yae;Kim, Tae-Woong
    • Journal of Korea Water Resources Association
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    • v.52 no.12
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    • pp.1001-1009
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    • 2019
  • Due to recent increasing heavy snow in Korea, the damage caused by heavy snow is also increasing. In Korea, there are many efforts including establishing disaster prevention measures to reduce the damage throughout the country, but it is difficult to establish the design criteria due to the characteristics of heavy snow. In this study, snowfall frequency analysis was performed to estimate design snow depths using observed snow depth data at Jinju, Changwon and Hapcheon stations. The conventional frequency analysis is sometime limted to apply to the snow depth data containing zero values which produce unrealistc estimates of distributon parameters. To overcome this problem, this study employed mixed distributions based on Lognormal, Generalized Pareto (GP), Generalized Extreme Value (GEV), Gamma, Gumbel and Weibull distribution. The results show that the mixed distributions produced smaller design snow depths than single distributions, which indicated that the mixed distributions are applicable and practical to estimate design snow depths.

Stand Structure of the Natural Broadleaved-Korean Pine Forests in Northeast China

  • Li, Fengri;Ma, Zhihai
    • Journal of Korean Society of Forest Science
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    • v.94 no.5 s.162
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    • pp.321-329
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    • 2005
  • Based on the data representing four typical Korean pine forest types, the age structure, DBH distribution, species composition, and forking rule were systemically analyzed for old-growth Korean pine forest in Liangshui Nature Reserve, northeast China. The age structure of Korean pine trees was strongly uneven-aged with one dominated peak following normal distribution, and age of trees varied from 100 to 180 years within a stand. The DBH and height differences in same age class (20 years) varied from 28 cm~64 cm and 5 to 20 m, respectively. Many conifer and hard wood species, such as spruce, fir, costata birch, basswood, oak, and elm, were mixed with dominated trees of Korean pine. The canopy of the old-growth Korean pine forest can be divided into two layers, and differences of mean age and height between Layer I and Layer II were ranged 80~150 years and 7~13 m, respectively. The Weibull function was used to model the diameter distribution and performed well to describe size-class distribution either with a single peak in over-story canopy and inverse J-shape in under-story canopy for old-growth Korean pine stands. The forking height of Korean pine trees ranged from 16m to 24 m (mean 19.4 m) and tree age about 120 to 160 years old. The results will provide a scientific basis to protect and recover the ecosystem of natural old-growth Korean pine and also provide the model in management of Korean pine plantation.

Influence of SF6/N2 Gas Mixture Ratios on the Lightning Streamer Propagation Characteristics of 22 kV MV Circuit Breaker

  • Gandhi, R.;Chandrasekar, S.;Nagarajan, C.
    • Journal of Electrical Engineering and Technology
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    • v.13 no.4
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    • pp.1663-1672
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    • 2018
  • In recent times, gas insulated medium voltage (MV) circuit breakers (CB) form a vital component in power system network, considering its advantages such as reduced size and safety margins. Gas insulation characteristics of circuit breakers are generally measured by lightning impulse (LI) test according to IEC standard 60060-1 as a factory routine test. Considering the environmental issues of $SF_6$ gas, many research works are being carried out towards the mixture of $SF_6$ gases for high voltage insulation applications. However, few reports are only available regarding the LI withstand and streamer propagation characteristics (at both positive and negative polarity of waveform) of $SF_6/N_2$ gas mixture insulated medium voltage circuit breakers. In this paper, positive and negative polarity LI tests are carried out on 22 kV medium voltage circuit breaker filled with $SF_6/N_2$ gas mixture at different gas pressures (1-5 bar) and at different gas mixture ratios. Important LI parameters such as breakdown voltage, streamer velocity, time to breakdown and acceleration voltage are evaluated with IEC standard LI ($1.2/50{\mu}s$) waveform. Weibull distribution analysis of LI breakdown voltage data is carried out and 50% probability breakdown voltage, scale parameter and shape parameter are evaluated. Results illustrate that the $25%SF_6+75%N_2$ gas filled insulation considerably enhances the LI withstand and breakdown strength of MV circuit breakers. LI breakdown voltage of circuit breaker under negative polarity shows higher value when compared with positive polarity. Results show that maintaining the gas pressure at 0.3 MPa (3 bar) with 10% $SF_6$ gas mixed with 90% $N_2$ will give optimum lighting impulse withstand performance of 22 kV MV circuit breaker.

Integrating Machine Reliability and Preventive Maintenance Planning in Manufacturing Cell Design

  • Das, Kanchan;Lashkari, R.S.;Sengupta, S.
    • Industrial Engineering and Management Systems
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    • v.7 no.2
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    • pp.113-125
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    • 2008
  • This paper presents a model for designing cellular manufacturing systems (CMS) by integrating system cost, machine reliability, and preventive maintenance (PM) planning. In a CMS, a part is processed using alternative process routes, each consisting of a sequence of visits to machines. Thus, a level of 'system reliability' is associated with the machines along the process route assigned to a part type. Assuming machine reliabilities to follow the Weibull distribution, the model assigns the machines to cells, and selects, for each part type, a process route which maximizes the overall system reliability and minimizes the total costs of manufacturing operations, machine underutilization, and inter-cell material handling. The model also incorporates a reliability based PM plan and an algorithm to implement the plan. The algorithm determines effective PM intervals for the CMS machines based on a group maintenance policy and thus minimizes the maintenance costs subject to acceptable machine reliability thresholds. The model is a large mixed integer linear program, and is solved using LINGO. The results point out that integrating PM in the CMS design improves the overall system reliability markedly, and reduces the total costs significantly.

Fitting Cure Rate Model to Breast Cancer Data of Cancer Research Center

  • Baghestani, Ahmad Reza;Zayeri, Farid;Akbari, Mohammad Esmaeil;Shojaee, Leyla;Khadembashi, Naghmeh;Shahmirzalou, Parviz
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.17
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    • pp.7923-7927
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    • 2015
  • Background: The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. Materials and Methods: In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. Results: The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Conclusions: Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.