Performance Evaluation of Existing Bridges under Vehicle Dynamic Effects

2013 ◽  
Vol 639-640 ◽  
pp. 42-53 ◽  
Author(s):  
Chun Sheng Cai ◽  
Wei Zhang ◽  
Lu Deng ◽  
Miao Xia
Keyword(s):  
Performance Evaluation ◽  
Life Cycle ◽  
Extreme Values ◽  
Value Theory ◽  
Vehicle Speed ◽  
Vehicle Dynamic ◽  
Dynamic Effects ◽  
Dynamic Amplification Factor ◽  
Maximum Displacement ◽  
Existing Bridges

This paper summarizes the recent work by the first author’s research group related to the performance evaluation of existing bridges under vehicle dynamic effects. Based on the data from short-term monitoring of existing bridges, a framework to estimate the extreme structure responses from the live load in a mean recurrence interval is developed in the first part. The Gumbel distribution of the extreme values was derived from an extreme value theory and Monte Carlo Simulation. In the second part, a framework of fatigue damage and reliability assessment for existing bridges is presented to include the effects of the progressively deteriorated road conditions and random dynamic vehicle loads in bridge’s life cycle. The random effects of vehicle speed and type, road profiles, and stress ranges are included. Studies have shown that the vehicle-induced dynamic allowance IM value prescribed by the AASHTO LRFD code may be underestimated under poor road surface conditions (RSCs) of some existing bridges. In addition, multiple dynamic stress ranges induced by vehicles cannot be included in the maximum displacement-based dynamic allowance IM values. In the third part of this paper, the reliability indices of a selected group of prestressed concrete girder bridges are calculated by modeling the IM explicitly as a random variable for different RSCs. Nevertheless, a reliability based dynamic amplification factor on stress ranges (DAFS) for fatigue design is proposed to include the fatigue damages from multiple stress range cycles due to each vehicle passage at varied vehicle speeds under various road conditions in the bridge’s life cycle.

scholarly journals THE FULL TAILS GAMMA DISTRIBUTION APPLIED TO MODEL EXTREME VALUES

2017 ◽  
Vol 47 (3) ◽  
pp. 895-917 ◽  
Author(s):  
Joan del Castillo ◽  
Jalila Daoudi ◽  
Isabel Serra
Keyword(s):  
Extreme Value Theory ◽  
Pareto Distribution ◽  
Extreme Values ◽  
Dispersion Model ◽  
Value Theory ◽  
Quantitative Modelling ◽  
Exponential Distributions ◽  
Exponential Dispersion Model ◽  
Aggregate Loss ◽  
Very High

AbstractIn this paper, we introduce the simplest exponential dispersion model containing the Pareto and exponential distributions. In this way, we obtain distributions with support (0, ∞) that in a long interval are equivalent to the Pareto distribution; however, for very high values, decrease like the exponential. This model is useful for solving relevant problems that arise in the practical use of extreme value theory. The results are applied to two real examples, the first of these on the analysis of aggregate loss distributions associated to the quantitative modelling of operational risk. The second example shows that the new model improves adjustments to the destructive power of hurricanes, which are among the major causes of insurance losses worldwide.

scholarly journals Predicting the change of hydraulic loads on bridges: a case study in Italy with a 100-year database

2019 ◽  
Author(s):  
Alessandro Pucci ◽  
Hélder S. Sousa ◽  
José C. Matos
Keyword(s):  
Climate Change ◽  
Climatic Variability ◽  
Value Theory ◽  
Peak Discharge ◽  
Greenhouse Gasses ◽  
Hydraulic Design ◽  
Design Loads ◽  
Hydrological Cycles ◽  
Existing Bridges

<p>Planet Earth is naturally subject to climatic variability, but over the recent decades extreme deviations have been observed. Climate change, as a manmade-induced process, is mainly due to the increase of greenhouse gasses emission. Global warming consequences drive also to an intensification of hydrological cycles, leading to more frequent and severe precipitations. In parallel, several bridges have collapsed in the last years due to extreme rainfalls. Although the impacts of climate change on built environment do not always present a direct cause-effect relation, analysis on specific parameters (as rain volume) that are inputs in bridge design, can clarify some aspects of this interaction. In this paper, the peak discharge variation of different rivers located in the northwest of Italy, within the last 100 years, is analyzed. A cluster analysis was performed to understand if the hydraulic design loads should be considered with a different intensity if the bridge had been built with reference to an up-to-date database, or if in the last decades, when the majority of these structures were built. The rainfall data was analyzed through classical techniques, such as the frequency-based statistical method, but without the stationary time hypothesis. In this case, the extreme value theory was used for the estimation of intensity-duration curve parameters. By introducing a second-order analysis, where random variables can change over time, an increase-trend of rainfall height was found, and the peak discharge was determined accordingly. The relevant parameters on the case-study area were preliminarily obtained through geographic information systems. The results evidenced that nowadays-floods parameters are significantly different from those of the past, and this behavior is escalated when high return period values are assumed. Furthermore, although hydraulic design loads are increasing, many existing bridges are not properly maintained, leading to an increased number of collapses.</p>

Tree-dependent extreme values: the exponential case

1990 ◽  
Vol 27 (01) ◽  
pp. 124-133 ◽  
Author(s):  
Vijay K. Gupta ◽  
Oscar J. Mesa ◽  
E. Waymire
Keyword(s):  
Branching Process ◽  
Extreme Values ◽  
Rooted Tree ◽  
Domain Of Attraction ◽  
Extreme Value Distribution ◽  
Value Theory ◽  
Extreme Value ◽  
Extinction Time ◽  
Brownian Excursion ◽  
Weighted Trees

The length of the main channel in a river network is viewed as an extreme value statistic L on a randomly weighted binary rooted tree having M sources. Questions of concern for hydrologic applications are formulated as the construction of an extreme value theory for a dependence which poses an interesting contrast to the classical independent theory. Equivalently, the distribution of the extinction time for a binary branching process given a large number of progeny is sought. Our main result is that in the case of exponentially weighted trees, the conditional distribution of n–1/2 L given M = n is asymptotically distributed as the maximum of a Brownian excursion. When taken with an earlier result of Kolchin (1978), this makes the maximum of the Brownian excursion a tree-dependent extreme value distribution whose domain of attraction includes both the exponentially distributed and almost surely constant weights. Moment computations are given for the Brownian excursion which are of independent interest.

Bio-electrochemical conversion of industrial wastewater-COD combined with downstream methanol synthesis – an economic and life cycle assessment

2018 ◽  
Vol 20 (12) ◽  
pp. 2742-2762 ◽  
Author(s):  
J. Streeck ◽  
C. Hank ◽  
M. Neuner ◽  
L. Gil-Carrera ◽  
M. Kokko ◽  
...  
Keyword(s):  
Life Cycle Assessment ◽  
Performance Evaluation ◽  
Life Cycle ◽  
Environmental Performance ◽  
Industrial Wastewater ◽  
Cell System ◽  
Electrolysis Cell ◽  
Microbial Electrolysis Cell ◽  
Electrochemical Conversion ◽  
Environmental Performance Evaluation

Herein, a techno-economic and environmental performance evaluation (i.e. Life Cycle Assessment (LCA)) of a 45 kW Microbial Electrolysis Cell system is presented in the context of industrial wastewater conversion.

Extreme values of phase-type and mixed random variables with parallel-processing examples

1999 ◽  
Vol 36 (01) ◽  
pp. 194-210 ◽  
Author(s):  
Sungyeol Kang ◽  
Richard F. Serfozo
Keyword(s):  
Parallel Processing ◽  
Asymptotic Distribution ◽  
Extreme Values ◽  
Random Variables ◽  
Extreme Value Distribution ◽  
Rates Of Convergence ◽  
Value Theory ◽  
Extreme Value ◽  
Independent Random Variables ◽  
Phase Type

A basic issue in extreme value theory is the characterization of the asymptotic distribution of the maximum of a number of random variables as the number tends to infinity. We address this issue in several settings. For independent identically distributed random variables where the distribution is a mixture, we show that the convergence of their maxima is determined by one of the distributions in the mixture that has a dominant tail. We use this result to characterize the asymptotic distribution of maxima associated with mixtures of convolutions of Erlang distributions and of normal distributions. Normalizing constants and bounds on the rates of convergence are also established. The next result is that the distribution of the maxima of independent random variables with phase type distributions converges to the Gumbel extreme-value distribution. These results are applied to describe completion times for jobs consisting of the parallel-processing of tasks represented by Markovian PERT networks or task-graphs. In these contexts, which arise in manufacturing and computer systems, the job completion time is the maximum of the task times and the number of tasks is fairly large. We also consider maxima of dependent random variables for which distributions are selected by an ergodic random environment process that may depend on the variables. We show under certain conditions that their distributions may converge to one of the three classical extreme-value distributions. This applies to parallel-processing where the subtasks are selected by a Markov chain.

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