A realistic resistance deterioration model for time-dependent reliability analysis of aging bridges

et al. 2019

Applied Sciences

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The deflections of retaining structures during deep excavation should be controlled below a predefined threshold in an attempt to mitigate the deformation-posed damage to the surrounding buildings and infrastructure facilities. In this paper, a new approach is presented to conducting deformation reliability assessments of retaining structures. The method is based on an extension of the classical first-passage reliability problem and is applied on the spatial scale of the retaining structures. With the proposed method, the in situ monitoring data and the associated measurement error can be easily incorporated, which accordingly improves the assessment accuracy. Moreover, the proposed method has a closed-form solution, which is beneficial for the computation efficiency and its practical application. The method was applied to assess the retaining structure reliability in a foundation excavation of a subway station in Fuzhou, China. The accuracy of the analytical results was verified through a comparison with those of Monte Carlo simulation. It was shown that the proposed method can represent well, the deformation-based safety level of retaining structures.

“…d n . Furthermore, employing the concept of "average variance" [49], the variance of Y(x) is computed as follows,…”

Section: Fitting the Variance Of Y(x)mentioning

confidence: 99%

Data-Driven Deformation Reliability of Retaining Structures in Deep Excavations Considering Measurement Error

et al. 2019

Applied Sciences

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“…, t n , respectively. While the structural deterioration process is indeed a complex non-stationary stochastic process (Dieulle et al, 2003;Saassouh et al, 2007;Wang et al, 2015), neither fully-correlated nor statistically independent by nature, revealed that the assumption of fully-correlated deterioration is reasonable for reliability analysis producing acceptable error. As a result, in this study, the resistance deterioration process is assumed to be a fully-correlated one, which means that the overall trajectory of deterioration will be determined as soon as the deterioration type and the deterioration value at any time are given.…”

Section: Structural Reliability Analysismentioning

confidence: 99%

“…(4)); in such a case, G(T ) follows an inverse-lognormal distribution. (4) Some studies have also used the Gamma process to model the resistance deterioration (Dieulle et al, 2003;Wang et al, 2015), with which G(T ) follows Gamma distribution. Now, taking into account the uncertainty associated with G(T ), supposing that the PDF of G(T ) is f G (g), Eq.…”

Section: Probabilistic Model Of Resistance Deteriorationmentioning

confidence: 99%

“…In these existing methods, the presence of the probability distribution of resistance deterioration is essentially necessary for structural reliability analysis when taking into account the uncertainty associated with the time-variant resistance. Practically, the main characteristics of resistance deterioration (e.g., the mean value and/or the standard deviation) can be obtained by either experimental laboratory data (Paik and Kim, 2012;Mohd and Paik, 2013;Ma et al, 2013;Mohd et al, 2014) or in-situ inspection following established standards or manuals (AASHTO, 2008;MOT, 2011;Wang et al, 2015). However, the probabilistic distribution of degraded resistance often remains unaddressed due to the limits of available data (Ellingwood, 2005).…”

Section: Introductionmentioning

confidence: 99%

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Estimating the time-dependent reliability of aging structures in the presence of incomplete deterioration information

J. Zhejiang Univ. Sci. A

Pang

et al. 2016

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The performance of an aging structure is commonly evaluated under the framework of reliability analysis, where the uncertainties associated with the structural resistance and loads should be taken into account. In practical engineering, the probability distribution of resistance deterioration is often inaccessible due to the limits of available data, although the statistical parameters such as mean value and standard deviation can be obtained by fitting or empirical judgments. As a result, an error of structural reliability may be introduced when an arbitrary probabilistic distribution is assumed for the resistance deterioration. With this regard, in this paper, the amount of reliability error posed by different choices of deterioration distribution is investigated, and a novel approach is proposed to evaluate the averaged structural reliability under incomplete deterioration information, which does not rely on the probabilistic weight of the candidate deterioration models. The reliability for an illustrative structure is computed parametrically for varying probabilistic models of deterioration and different resistance conditions, through which the reliability associated with different deterioration models is compared, and the application of the proposed method is illustrated.

“…The Gamma process has been widely used to describe the resistance deterioration (the difference between the initial and the degraded resistances) of aging bridges (Dieulle et al 2003;Saassouh et al 2007;van Noortwijk et al 2007;Li et al 2015;Wang et al 2015;Wang et al 2019), which is, by nature, a non-decreasing process and enables the autocorrelation of the resistance deterioration process on the temporal scale to be considered. The monotonicity of a Gamma process is guaranteed by its nonnegative and independent increments.…”

Section: Introductionmentioning

confidence: 99%

A stochastic process model for resistance deterioration of aging bridges

2020

ABEN

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The serviceability and safety level of bridges often deteriorates due to the environmental or operational conditions. A stochastic deterioration model is of essential importance for describing the time-variation of bridge performance (e.g., stiffness and strength), and for use in the estimate of bridge reliability under a probabilistic framework. In this context, the Gamma process has been widely used to model the resistance deterioration of aging bridges, yet suffers from the deficiency that the statistical characteristics of the process (namely mean value, variance and autocorrelation) are not mutually independent. This paper presents a new stochastic model for bridge resistance deterioration. As a modified version of the Gamma process-based one, the proposed model includes a new parameter that can release the dependence of the process autocorrelation and variance on the mean value. The impact of the new deterioration model on the time-dependent reliability of aging bridges is studied.