Stochastic modeling and statistical analysis of fatigue tests on prestressed concrete beams under cyclic loadings
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Date
2015
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Abstract
To evaluate the fatigue behavior of prestressed concrete, bridges for instance, it is necessary
to determine the built in tendons’ fatigue strength. Therefore, prestressing steel samples
(strands), obtained from an existing bridge built in 1957, were examined and tested by TU
Dortmund University, see [1, 2]. Additionally, similar prestressing steels were tested in comparable
experiments. As large experiments on prestressed concrete beams under cyclic load with small
stress range are very time-consuming and expensive, an early prediction of failure trend in the
experiment is desirable. Here, it is shown that a crack width function can be evolved dependent
on the process of single wire failures. This process will differ for each experiment because of the
randomness of single wire failure. Description of this uncertainty is the first step and is achieved
by a predictive distribution for the counting process of wire failure. The second step is to include
these results into the model for the crack width process for which a nonlinear regression model
based on a physically evolved function depending on the counting process is suitable. For both
modeling steps, we present a Bayesian estimation and prediction procedure.
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Keywords
crack growth, Bayesian estimation and prediction, nonlinear regression, counting process, long-term tests, prestressing steel, fatigue experiments