A stochastic process model for resistance deterioration of aging bridges

Cao Wang

doi:10.1186/s43251-020-00003-w

Abstract

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.

Highlights

1 Introduction In-service bridges often suffer from the deterioration of performance subjected to aggressive environmental or operational conditions, which may further decline the bridge safety level below the baseline as assumed in design
It is of essential importance to model the deterioration process of aging bridges reasonably for use in the estimate of structural service reliability, providing a decision-aid tool for maintenance and repair measures for the bridges (Mori and Ellingwood 1993; Enright and Frangopol 1998; Stewart and Val 1999; OBrien et al 2014)
(2020) 1:3 scale parameter (Kahle et al 2016). This fact, indicates that both the autocorrelation and the variance of a Gamma process are dependent on the mean value of the process

Summary

Introduction

In-service bridges often suffer from the deterioration of performance (e.g., stiffness and strength) subjected to aggressive environmental or operational conditions, which may further decline the bridge safety level below the baseline as assumed in design. Such dependence may halter the applicability of a Gamma process-based deterioration model in structural reliability assessment, especially for the cases where observed data are available to calibrate the unknown parameters in the deterioration process.

Results

Conclusion