963 resultados para MODIFIED WEIBULL DISTRIBUTION


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The use of mobile phones while driving is more prevalent among young drivers—a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q Advanced Driving Simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver’s peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21 to 26 years old and split evenly by gender. Drivers’ reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver’s age, license type (Provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted presents a significant and measurable safety concern that will undoubtedly persist unless mitigated.

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This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

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The cotton strip assay (CSA) is an established technique for measuring soil microbial activity. The technique involves burying cotton strips and measuring their tensile strength after a certain time. This gives a measure of the rotting rate, R, of the cotton strips. R is then a measure of soil microbial activity. This paper examines properties of the technique and indicates how the assay can be optimised. Humidity conditioning of the cotton strips before measuring their tensile strength reduced the within and between day variance and enabled the distribution of the tensile strength measurements to approximate normality. The test data came from a three-way factorial experiment (two soils, two temperatures, three moisture levels). The cotton strips were buried in the soil for intervals of time ranging up to 6 weeks. This enabled the rate of loss of cotton tensile strength with time to be studied under a range of conditions. An inverse cubic model accounted for greater than 90% of the total variation within each treatment combination. This offers support for summarising the decomposition process by a single parameter R. The approximate variance of the decomposition rate was estimated from a function incorporating the variance of tensile strength and the differential of the function for the rate of decomposition, R, with respect to tensile strength. This variance function has a minimum when the measured strength is approximately 2/3 that of the original strength. The estimates of R are almost unbiased and relatively robust against the cotton strips being left in the soil for more or less than the optimal time. We conclude that the rotting rate X should be measured using the inverse cubic equation, and that the cotton strips should be left in the soil until their strength has been reduced to about 2/3.

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Braking is a crucial driving task with a direct relationship with crash risk, as both excess and inadequate braking can lead to collisions. The objective of this study was to compare the braking profile of young drivers distracted by mobile phone conversations to non-distracted braking. In particular, the braking behaviour of drivers in response to a pedestrian entering a zebra crossing was examined using the CARRS-Q Advanced Driving Simulator. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free, and handheld. In addition to driving the simulator, each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The drivers were 18–26 years old and split evenly by gender. A linear mixed model analysis of braking profiles along the roadway before the pedestrian crossing revealed comparatively increased decelerations among distracted drivers, particularly during the initial 20 kph of deceleration. Drivers’ initial 20 kph deceleration time was modelled using a parametric accelerated failure time (AFT) hazard-based duration model with a Weibull distribution with clustered heterogeneity to account for the repeated measures experiment design. Factors found to significantly influence the braking task included vehicle dynamics variables like initial speed and maximum deceleration, phone condition, and driver-specific variables such as licence type, crash involvement history, and self-reported experience of using a mobile phone whilst driving. Distracted drivers on average appear to reduce the speed of their vehicle faster and more abruptly than non-distracted drivers, exhibiting excess braking comparatively and revealing perhaps risk compensation. The braking appears to be more aggressive for distracted drivers with provisional licenses compared to drivers with open licenses. Abrupt or excessive braking by distracted drivers might pose significant safety concerns to following vehicles in a traffic stream.

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Large sized power transformers are important parts of the power supply chain. These very critical networks of engineering assets are an essential base of a nation’s energy resource infrastructure. This research identifies the key factors influencing transformer normal operating conditions and predicts the asset management lifespan. Engineering asset research has developed few lifespan forecasting methods combining real-time monitoring solutions for transformer maintenance and replacement. Utilizing the rich data source from a remote terminal unit (RTU) system for sensor-data driven analysis, this research develops an innovative real-time lifespan forecasting approach applying logistic regression based on the Weibull distribution. The methodology and the implementation prototype are verified using a data series from 161 kV transformers to evaluate the efficiency and accuracy for energy sector applications. The asset stakeholders and suppliers significantly benefit from the real-time power transformer lifespan evaluation for maintenance and replacement decision support.

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A constitutive modeling approach for shape memory alloy (SMA) wire by taking into account the microstructural phase inhomogeneity and the associated solid-solid phase transformation kinetics is reported in this paper. The approach is applicable to general thermomechanical loading. Characterization of various scales in the non-local rate sensitive kinetics is the main focus of this paper. Design of SMA materials and actuators not only involve an optimal exploitation of the hysteresis loops during loading-unloading, but also accounts for fatigue and training cycle identifications. For a successful design of SMA integrated actuator systems, it is essential to include the microstructural inhomogeneity effects and the loading rate dependence of the martensitic evolution, since these factors play predominant role in fatigue. In the proposed formulation, the evolution of new phase is assumed according to Weibull distribution. Fourier transformation and finite difference methods are applied to arrive at the analytical form of two important scaling parameters. The ratio of these scaling parameters is of the order of 10(6) for stress-free temperature-induced transformation and 10(4) for stress-induced transformation. These scaling parameters are used in order to study the effect of microstructural variation on the thermo-mechanical force and interface driving force. It is observed that the interface driving force is significant during the evolution. Increase in the slopes of the transformation start and end regions in the stress-strain hysteresis loop is observed for mechanical loading with higher rates.

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Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.

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The time–history of the performance of a system is treated as a stochastic corrective process, in which deterioration due to aging is counteracted at brief maintenance checks. Using a diffusion approximation for the deterioration, simple models are proposed for describing maintenance either by component replacement or by performance restoration. Equilibrium solutions of the models show that the performance has a probability distribution with exponential tails: the uncritical use of Gaussians can grossly underestimate the probability of poor performance. The proposed models are supported by recent observational evidence on aircraft track-keeping errors, which are shown to follow the modified exponential distribution derived here. The analysis also brings out the relation between the deterioration characteristics of the system and the intensity of the maintenance effort required to achieve a given performance reliability.

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Following Weisskopf, the kinematics of quantum mechanics is shown to lead to a modified charge distribution for a test electron embedded in the Fermi-Dirac vacuum with interesting consequences.

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Metsäsuunnittelussa tarvittavan metsävaratiedon keräämisessä ollaan Suomessa siirtymässä kuvioittaisesta arvioinnista laserkeilaus- ja ilmakuvapohjaiseen kaukokartoitukseen. Tämän tutkimuksen tarkoitus oli selvittää kuvion kokonaistilavuuden ja läpimittajakauman ennustamisen tarkkuus koealan metsikkö- ja puustotunnuksista MSN-, PRM-, ML- ja FMM-menetelmiä sekä Weibull-jakaumaa hyödyntäen seuraavilla tavoilla: 1. PRM-menetelmällä hilatasolla, 2. PRMmenetelmällä kuviotasolla, 3. ML-menetelmällä hilatasolla ja 4. ML-menetelmällä kuviotasolla. Lisäksi kuvion kokonaistilavuuden ennustamisen tarkkuus selvitettiin hyödyntäen kuviolle tuotettua runkolukusarjaa. Tulokset laskettiin puulajikohtaisesti männylle, kuuselle, koivulle ja muille puulajeille. Puulajien tulokset laskettiin kuviotasolla yhteen. Lisäksi selvitettiin menetelmien laskenta-ajan ja tallennustilan tarve. Tutkimuksen aineistona käytettiin Hämeen ammattikorkeakoulun Evon toimipisteen metsistä mitattuja kiinteäsäteisiä ympyräkoealoja, joita oli 249 kappaletta. Hakkuukoneella mitattiin 12kuvion, joiden pinta-alat vaihtelivat välillä 0,2 – 1,94 hehtaaria, puustotiedot. Aluepohjaisen laserkeilausaineiston pulssin tiheys oli 1,8/m2 ja ilmakuvien pikselikoko 0,5 metriä. Kuvion kokonaistilavuus ennustettiin tai estimoitiin laserkeilaus- ja ilmakuva-aineiston piirteiden avulla koealojen puustotunnuksista. Tulokset laskettiin erikseen kaikille kuvioille ja kuvioille, joiden pinta-ala oli yli 0,5 hehtaaria. Yli 0,5 hehtaarin kuvioita oli 8 kappaletta. Kuvion hilojen naapureina käytettiin 1 - 10 koealaa. Menetelmästä ja naapurien määrästä riippuen kokonaistilavuuden suhteellinen RMSE ja harha vaihtelivat välillä 20,76 – 52,86 prosenttia ja -12,04 – 46,54 prosenttia. Vastaavat luvut yli 0,5 hehtaarin kuvioilla olivat 6,74 – 59,41 prosenttia ja -8,04 – 49,59 prosenttia. Laskenta-aika vaihteli menetelmien ja käytettyjen naapurien määrän mukaan voimakkaasti. Kehittyneemmällä ohjelmoinnilla ja ohjelmistolla laskenta-ajat voivat laskea merkittävästi. Tallennustila ei testatuilla menetelmillä ole rajoittava tekijä laajassakaan mittakaavassa. Läpimittajakauman perusteella PRM-menetelmä ennustaa puulajille erittäin kapean läpimittajakauman, jos koeala koostuu vain muutamasta lähes samankokoisesta puusta. Tämä vaikutti tuloksiin erityisesti menetelmällä PRM2.

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Accelerated aging experiments have been conducted on a representative oil-pressboard insulation model to investigate the effect of constant and sequential stresses on the PD behavior using a built-in phase resolved partial discharge analyzer. A cycle of the applied voltage starting from the zero of the positive half cycle was divided into 16 equal phase windows (Φ1 to Φ16) and partial discharge (PD) magnitude distribution in each phase was determined. Based on the experimental results, three stages of aging mechanism were identified. Gumbel's extreme value distribution of the largest element was used to model the first stage of aging process. Second and subsequent stages were modeled using two-parameter Weibull distribution. Spearman's non-parametric rank correlation test statistic and Kolmogrov-Smirnov two sample test were used to relate the aging process of each phase with the corresponding process of the full cycle. To bring out clearly the effect of stress level, its duration and test procedure on the distribution parameters and hence of the aging process, non-parametric ANOVA techniques like Kruskal-Wallis and Fisher's LSD multiple comparison tests were used. Results of the analysis show that two phases (Φ13 and Φ14) near the vicinity of the negative voltage peak were found to contribute significantly to the aging process and their aging mechanism also correlated well with that of the corresponding full cycle mechanism. Attempts have been made to relate these results with the published work of other workers

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In heterogeneous brittle media, the evolution of damage is strongly influenced by the multiscale coupling effect. To better understand this effect, we perform a detailed investigation of the damage evolution, with particular attention focused on the catastrophe transition. We use an adaptive multiscale finite-element model (MFEM) to simulate the damage evolution and the catastrophic failure of heterogeneous brittle media. Both plane stress and plane strain cases are investigated for a heterogeneous medium whose initial shear strength follows the Weibull distribution. Damage is induced through the application of the Coulomb failure criterion to each element, and the element mesh is refined where the failure criterion is met. We found that as damage accumulates, there is a stronger and stronger nonlinear increase in stress and the stress redistribution distance. The coupling of the dynamic stress redistribution and the heterogeneity at different scales result in an inverse cascade of damage cluster size, which represents rapid coalescence of damage at the catastrophe transition.

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In heterogeneous brittle media, the evolution of damage is strongly influenced by the multiscale coupling effect. To better understand this effect, we perform a detailed investigation of the damage evolution, with particular attention focused on the catastrophe transition. We use an adaptive multiscale finite-element model (MFEM) to simulate the damage evolution and the catastrophic failure of heterogeneous brittle media. Both plane stress and plane strain cases are investigated for a heterogeneous medium whose initial shear strength follows the Weibull distribution. Damage is induced through the application of the Coulomb failure criterion to each element, and the element mesh is refined where the failure criterion is met. We found that as damage accumulates, there is a stronger and stronger nonlinear increase in stress and the stress redistribution distance. The coupling of the dynamic stress redistribution and the heterogeneity at different scales result in an inverse cascade of damage cluster size, which represents rapid coalescence of damage at the catastrophe transition.

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海洋石油平台在服役期内,由于受到各种环境载荷的交变作用,其受力的焊接构件不可避免地会出现疲劳裂纹。对出现的疲劳裂纹进行补焊修复,可以延长平台的使用期,带来巨大的经济和社会效益。本文通过实验研究,考察了多次补焊对海洋平台用高强度钢焊接接头疲劳性能的影响,以及是否可以通过TIG熔修工艺的采用提高补焊构件的疲劳寿命,达到延长补焊后平台的使用寿命,减少补焊次数的目的。本文涉及的主要研究内容如下:1、考察了多次补焊对焊接接头疲劳寿命的影响。通过对平台用高强度钢焊接接头初焊试样,以及重复三次补焊试样的疲劳实验,得到了各次补焊试样在对数正态分布和威布尔分布下的寿命估算式和考虑了存活率的R-S-N曲线。对实验结果进行了比较和分析,从而考察了多次补焊对焊接接头疲劳性能的影响。2、在每次补焊后,由于焊趾外移造成了焊趾角的变化,使得焊趾处的应力集中系数发生了变化。本文采用有限元方法计算了试样的应力场分布,得到了焊趾处的应力集中系数与焊趾角的关系。考虑到应力集中系数的变化后,对多次补焊试样疲劳实验的实验数据进行了重新处理。3、考察了多次补焊熔修对焊接接头疲劳寿命的影响。本文通过对平台用高强度钢焊接接头补焊及补焊熔修试样的疲劳实验,得到了多次补焊和补焊熔修试样对数正态分布和威布尔分布下的寿命估算式和考虑了存活率的R-S-N曲线。对实验结果进行了比较和分析,从而考察了补焊后采用TIG熔修工艺对焊接接头疲劳性能的影响。4、一次补焊后进行熔修处理可以极大的改善试样的疲劳性能,提高试样的疲劳寿命。但这一结果是在平焊位条件下得出了。为了将这一结果用于实际,还要考察实际操作中大量采用的立焊位条件下熔修的效果。本文完成了立焊位条件下补焊及补焊熔修试样的疲劳实验,得到了相应的S-N曲线。5、疲劳实验数据的处理中,大量采用威布尔分布作为数据统计的分布类型。但由于威布尔分布具有三个参数,给求解带来一定的困难。本文提出一种以在威布尔坐标纸上,数据分布的线形相关系数作为判据的求解威布尔参数的方法,并通过程序加以实现。为了对疲劳实验数据的处理更加方便和直观,编制了“疲劳实验数据处理程序“,将对疲劳实验数据的编辑、分布参数的求解、不同存活率下的疲劳寿命估算和各种分布类型图以及R-S-N曲线的绘制工作包括在该程序中。

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在白以龙小组已有工作的基础上,利用他们提出的简化的耦合斑图模型,几种可能的应力重分配模型在该论文中得到了进一步的讨论。通过不同的应力重分配模型,我们发现了该类演化过程中的三个一般规律,这些规律对于类似的动力过程的预报(例如,非均匀介质的破坏)提供了线索。首先,我们采用系综统计的方法,对相同宏观参量的大量样本的强度分布作了考察,结果表明:宏观强度的统计结果可以非常好的拟合为Weibull分布,且其Weibull模数与系统的大小、应力重分配的方式以及细观单元的强度分布相关。其次,在模拟过程中,对演化过程中的能量释放、损伤事件的统计发现,它们存在标度行为,而且这一标度主要归因于灾变点附近的损伤事件。这一现象表明这一转变具有某种临界特征。最后,对于我们模型中的动力学过程,我们发现了灾变预报的线索。从样本演化过程 中的能量释放规律来看,我们发现有两件事是有意义的:一是辨别出主破坏的发生点(在这一时修,系统中的大部分能量得到释放);另外,给出转变点(整体稳定转化为演化诱致灾变)的预报。对前一个问题,我们通过考察系统在GS和EIC段的应力损伤涨落特征可以给出回答,通常,在EIC段的最大应力涨落(通常出现在主破坏过程中)比在GS过程中的最大应力涨落高一个数量级,根据这一差异,可以设立一个应力涨落的警戒值来判断系统所处的演化状态。对于后者,受到地震预报中采用的加卸载响应比(LURR)的启发,我们通过对系统中的外回转应力或损伤单元施加一个微增扰动,然后,根据系统在扰动前后释放的能量和相应的扰动,就可以得到临界敏感系数,临界敏感系数在灾变点附近迅速增加,在灾变点之迅速下降到1附近-我们称这一特征为临界敏感性。不同的应力重分配模型下得到了类似的现象,由此看来,对于 类似的动力学过程,临界敏感性是一个一般的特征。这一特征可能为我们对非均匀脆性介质的破坏提供线索。