scholarly journals Survival Analysis of Fatigue and Rutting Failures in Asphalt Pavements

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Pabitra Rajbongshi ◽  
Sonika Thongram
Keyword(s):  
Survival Analysis ◽  
Failure Rate ◽  
Failure Time ◽  
Dependent Random Variable ◽  
Survival Function ◽  
Random Variable ◽  
Asphalt Pavements ◽  
Rate Period ◽  
Pavement Structures ◽  
Probability Density Function Pdf

Fatigue and rutting are two primary failure mechanisms in asphalt pavements. The evaluations of fatigue and rutting performances are significantly uncertain due to large uncertainties involved with the traffic and pavement life parameters. Therefore, deterministically it is inadequate to predict when an in-service pavement would fail. Thus, the deterministic failure time which is known as design life (yr) of pavement becomes random in nature. Reliability analysis of such time (t) dependent random variable is the survival analysis of the structure. This paper presents the survival analysis of fatigue and rutting failures in asphalt pavement structures. It is observed that the survival of pavements with time can be obtained using the bathtub concept that contains a constant failure rate period and an increasing failure rate period. The survival function (S(t)), probability density function (pdf), and probability distribution function (PDF) of failure time parameter are derived using bathtub analysis. It is seen that the distribution of failure time follows three parametric Weibull distributions. This paper also works out to find the most reliable life (YrR) of pavement sections corresponding to any reliability level of survivability.

scholarly journals On the control of the difference between two Brownian motions: a dynamic copula approach

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Thomas Deschatre
Keyword(s):  
Cumulative Distribution Function ◽  
Survival Function ◽  
Random Variable ◽  
Cumulative Distribution ◽  
Gaussian Copula ◽  
Brownian Motions ◽  
Dynamic Copula ◽  
Copula Approach ◽  
The Difference ◽  
The Right

AbstractWe propose new copulae to model the dependence between two Brownian motions and to control the distribution of their difference. Our approach is based on the copula between the Brownian motion and its reflection. We show that the class of admissible copulae for the Brownian motions are not limited to the class of Gaussian copulae and that it also contains asymmetric copulae. These copulae allow for the survival function of the difference between two Brownian motions to have higher value in the right tail than in the Gaussian copula case. Considering two Brownian motions B1t and B2t, the main result is that the range of possible values for is the same for Markovian pairs and all pairs of Brownian motions, that is with φ being the cumulative distribution function of a standard Gaussian random variable.

Bayesian Nonparametric Estimation of Failure Rates with Censored Data

1983 ◽  
Vol 32 (1-2) ◽  
pp. 79-90 ◽  
Author(s):  
J. S. Rao ◽  
R. C. Tiwari
Keyword(s):  
Failure Time ◽  
Dirichlet Distribution ◽  
Survival Function ◽  
Fixed Time ◽  
Bayes Estimation ◽  
Time Interval ◽  
Failure Rates ◽  
Failure Time Distribution ◽  
Accelerated Life ◽  
Bayesian Nonparametric Estimation

The failure time distribution is estimated in the nonparametric context when some of tbe observations arc censored. The time interval is partitioned into fixed class intervals, and number of failures and number censored in each of these intervals are observed. Using a Dirichlet distribution as the prior, the resulting estimates of the survival function and the failure rate have a nice and simple form. If instead of the fixed time intervals, one uses the “natural” intervals formed by the observed failure times, this gives essentially the same results as in Ferauson IUld Phadia (1977), Susarla and Van Ryzin (1976), but in a much simpler way. Bayes estimation under the increasins and decreasing failure rates is also considered, and applications to accelerated life testing are discussed.

scholarly journals Long-Term Performance of Pavement Structures with Cold In-Place Recycled Base Course

2021 ◽  
Vol 16 (2) ◽  
pp. 48-65
Author(s):  
Audrius Vaitkus ◽  
Judita Gražulytė ◽  
Andrius Baltrušaitis ◽  
Jurgita Židanavičiūtė ◽  
Donatas Čygas
Keyword(s):  
Asphalt Pavement ◽  
Asphalt Mixture ◽  
Asphalt Pavements ◽  
Recycled Asphalt ◽  
Binding Agents ◽  
Pavement Structure ◽  
Pavement Structures ◽  
Base Course ◽  
Surface Distress ◽  
Foamed Bitumen

Properly designed and maintained asphalt pavements operate for ten to twenty-five years and have to be rehabilitated after that period. Cold in-place recycling has priority over all other rehabilitation methods since it is done without preheating and transportation of reclaimed asphalt pavement. Multiple researches on the performance of cold recycled mixtures have been done; however, it is unclear how the entire pavement structure (cold recycled asphalt pavement overlaid with asphalt mixture) performs depending on binding agents. The main objective of this research was to evaluate the performance of cold in-place recycled asphalt pavements considering binding agents (foamed bitumen in combination with cement or only cement) and figure out which binder leads to the best pavement performance. Three road sections rehabilitated in 2000, 2003, and 2005 were analysed. The performance of the entire pavement structure was evaluated in terms of the International Roughness Index, rut depth, and pavement surface distress in 2013 and 2017.

scholarly journals ДОСЛІДЖЕННЯ ПОКАЗНИКА ЕФЕКТИВНОСТІ ЕКСПЛУАТАЦІЇ ЗАСОБІВ ВИМІРЮВАЛЬНОЇ ТЕХНІКИ МЕТОДОМ КОМПʼЮТЕРНОГО МОДЕЛЮВАННЯ

2020 ◽  
pp. 166-169
Author(s):  
Олександр Володимирович Томашевський ◽  
Геннадій Валентинович Сніжной
Keyword(s):  
Computer Simulation ◽  
Distribution Function ◽  
Normal Distribution ◽  
Failure Rate ◽  
Random Variable ◽  
Operational Efficiency ◽  
Distribution Law ◽  
Maintenance System ◽  
Wide Range ◽  
Calibration Interval

The operational efficiency of measuring equipment (ME) is important in determining the cost of maintaining ME. To characterize the operational efficiency of the ME, an efficiency indicator has been introduced, an increase of which will reduce costs caused by the release of defective products due to the use of ME with unreliable indications. Over time, the ME parameters change under the influence of external factors and the ME aging processes inevitably occur, as a result of which the parameters of the ME metrological service system change. Therefore, in the general case, the parameters of the metrological maintenance system of ME should be considered as random variables. Accordingly, the efficiency indicator of measuring instruments is also a random variable, for the determination of which it is advisable to apply the methods of mathematical statistics and computer simulation. The performance indicator depends on the parameters of the metrological maintenance ME system, such as the calibration interval, the time spent by the ME on metrological maintenance, and the likelihood of ME failure-free operation. As a random variable, the efficiency indicator has a certain distribution function. To determine the distribution function of the efficiency indicator and the corresponding statistical characteristics, a computer simulation method was used. A study was made of the influence on the indicator of the effectiveness of the parameters of the metrological maintenance system ME (interesting interval, the failure rate of ME). The value of the verification interval and the failure rate of MEs varied over a wide range typical of real production. The time spent by ME on metrological services is considered as a random variable with a normal distribution law. To obtain random numbers with a normal distribution law, the Box-Muller method is used. After modeling, the statistical processing of the obtained results was done. It is shown that in real production, the efficiency indicator has a normal distribution law and the value of the efficiency indicator with an increase in the calibration interval does not practically change.

Survival analysis

2020 ◽  
pp. 181-218
Author(s):  
Bendix Carstensen
Keyword(s):  
Survival Analysis ◽  
Competing Risks ◽  
Cox Model ◽  
Survival Function ◽  
Event Analysis ◽  
Time To Event ◽  
Poisson Models ◽  
Kaplan Meier ◽  
Analysis Survival ◽  
Event Rates

This chapter describes survival analysis. Survival analysis concerns data where the outcome is a length of time, namely the time from inclusion in the study (such as diagnosis of some disease) till death or some other event — hence the term 'time to event analysis', which is also used. There are two primary targets normally addressed in survival analysis: survival probabilities and event rates. The chapter then looks at the life table estimator of survival function and the Kaplan–Meier estimator of survival. It also considers the Cox model and its relationship with Poisson models, as well as the Fine–Gray approach to competing risks.

Moment-Based Hybrid Polynomial Chaos Method for Interval and Random Uncertain Analysis of Periodical Composite Structural-Acoustic System with Multi-Scale Parameters

2020 ◽  
pp. 2050041
Author(s):  
Ning Chen ◽  
Jiaojiao Chen ◽  
Shengwen Yin
Keyword(s):  
Polynomial Chaos ◽  
Random Variable ◽  
Acoustic System ◽  
Passenger Compartment ◽  
Scale Parameters ◽  
Multi Scale ◽  
Arbitrary Polynomial ◽  
Random Moment ◽  
The Moment ◽  
Probability Density Function Pdf

An interval and random moment-based arbitrary polynomial chaos method (IRMAPCM) is proposed in this paper for the analysis of periodical composite structural-acoustic systems with multi-scale uncertain-but-bounded parameters. In IRMAPCM, the response of structural-acoustic system is approximated as moment-based arbitrary polynomial chaos (maPC) expansion. IRMAPCM can construct the polynomial basis according to the moment of the random variable without knowing the Probability Density Function (PDF), which can avoid the errors introduced by estimating the PDF. Numerical examples of a hexahedral box and an automobile passenger compartment are given to investigate the effectiveness of IRMAPCM for the prediction of the sound pressure response of structural-acoustic systems.

scholarly journals Investigating Social Contextual Factors in Remaining-Time Predictive Process Monitoring—A Survival Analysis Approach

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 267 ◽  
Author(s):  
Niyi Ogunbiyi ◽  
Artie Basukoski ◽  
Thierry Chaussalet
Keyword(s):  
Survival Analysis ◽  
Process Monitoring ◽  
Contextual Factors ◽  
Survival Function ◽  
Analysis Approach ◽  
Contextual Features ◽  
Monitoring Framework ◽  
Predictive Process ◽  
The Impact ◽  
Remaining Time

Predictive process monitoring aims to accurately predict a variable of interest (e.g., remaining time) or the future state of the process instance (e.g., outcome or next step). The quest for models with higher predictive power has led to the development of a variety of novel approaches. However, though social contextual factors are widely acknowledged to impact the way cases are handled, as yet there have been no studies which have investigated the impact of social contextual features in the predictive process monitoring framework. These factors encompass the way humans and automated agents interact within a particular organisation to execute process-related activities. This paper seeks to address this problem by investigating the impact of social contextual features in the predictive process monitoring framework utilising a survival analysis approach. We propose an approach to censor an event log and build a survival function utilising the Weibull model, which enables us to explore the impact of social contextual factors as covariates. Moreover, we propose an approach to predict the remaining time of an in-flight process instance by using the survival function to estimate the throughput time for each trace, which is then used with the elapsed time to predict the remaining time for the trace. The proposed approach is benchmarked against existing approaches using five real-life event logs and it outperforms these approaches.

Nonparametric Survival Analysis of Non-Motor Vehicles Violation in Signal Intersection

2015 ◽  
Vol 713-715 ◽  
pp. 2115-2118 ◽  
Author(s):  
Pan Hao ◽  
Wei Cheng
Keyword(s):  
Survival Analysis ◽  
Behavior Analysis ◽  
Motor Vehicle ◽  
Survival Function ◽  
Reference Value ◽  
Motor Vehicles ◽  
Analysis Method ◽  
Street Crossing ◽  
Traffic Characteristics ◽  
Traffic Behavior

The research objectives were to investigate non-motor vehicle violation in signal intersection by studying behavior analysis. Non-motor vehicles’ street-crossing behavior was examined by modeling the non-motor vehicles waiting time survival function at signalized crosswalk through survival analysis method. Statistical and analysis of the filtered traffic parameters such as drivers, road conditions and other factors on the age obtained regularities of non-motor vehicles violation and a contrast and reference value with pedestrians’ violation serving as evaluation of the crowd and traffic characteristics for non-motor vehicles violation which can be used on other similar traffic behavior analysis and has some reference value.

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