Elsevier

Thin-Walled Structures

Volume 49, Issue 1, January 2011, Pages 157-166
Thin-Walled Structures

Ultimate strength reliability analysis of corroded steel-box girder bridges

https://doi.org/10.1016/j.tws.2010.09.001Get rights and content

Abstract

Structural reliability theory is a useful tool for estimating the risks associated with deteriorating structures. The aim of this study is to develop and demonstrate a procedure for the assessment of box girder bridge ultimate strength reliability with the degradation of plate members due to general corrosion taken into account. A probabilistic model for ultimate steel-box girder strength is established on the basis of an analytic formula that considers corrosion-related, time-dependent strength degradation. The study involves the selection of representative structures, formulation of limit state functions, development of resistance models for corroded steel-box girders, development of load models, development of a reliability analysis method, reliability analysis of the selected bridges and development of the time-dependant reliability profiles, including deterioration due to corrosion. The results of this study can be used for the better prediction of the service life of deteriorating steel-box girder bridges and the development of optimal reliability-based maintenance strategies.

Introduction

Evaluations of existing steel bridge girders become more important with natural aging, increased load spectra, deterioration due to corrosion and other problems. Bridge structures exposed to aggressive environmental conditions are subject to time-variant changes in resistance. There is therefore a need for evaluation procedures that produce accurate predictions of the load-carrying capacity and reliability of bridge structures to allow rational decisions to be made about repair, rehabilitation and expected life-cycle costs. The efficient maintenance, repair and rehabilitation of existing bridges require the development of a methodology that allows for the accurate evaluation of load-carrying capacity and prediction of remaining life [1], [2], [3], [4].

Many of the factors that determine the performance of deteriorating structures have a high degree of uncertainty. Probability and statistics provide a framework for dealing with such uncertainties. Structural reliability analysis can be employed to calculate the probability of the limit state failure of structural members or structures at any time during their service life. The use of such analysis for the assessment of existing structures has been on the increase, as it minimizes the costs of maintenance and repair [3], [4], [5].

Deterioration models make it possible to establish a reliability time profile for a structure. The engineer then has to decide the point at which the structure becomes unsafe. To do so, one must establish a reliability index that can be used as the acceptable level below which the structure is considered to be unsafe. At present, no clear and exact guidelines are available for establishing this acceptance level; therefore, engineering judgment and experience are required. System models are generally used for reliability analysis of the strength failure of bridges. However, because the rehabilitation and repair of the bending moment or shear failure of a steel bridge is usually not the result of structure collapse, but rather of local limit state failure, element-level reliability analysis may be more reasonable than system-level reliability analysis in cases of the ultimate strength of steel or concrete bridges [5]. As has been observed in several studies (e.g. [6]), bending failure is the dominant failure mode for majority of steel girders, and ultimate moment resistance is considered in this study.

This paper will be useful for practicing engineers who need to employ reliability analysis in practical applications. The example presented herein demonstrates the procedures that are required to calculate the latest time to repair intervention for a number of deteriorating steel-box beams supporting a bridge. The paper considers the viewpoint of practicing engineers, and using a bridge-specific deterioration model highlights the problems associated with determining the latest such intervention for a sample bridge substructure. The experience gained and the difficulties faced by practicing engineers in using this method of analysis are also presented.

Section snippets

Corrosion mechanics and corrosion rate modeling

This paper focuses on the deterioration of steel bridges caused by corrosion. To predict the likely corrosion damage tolerance a priori, it is necessary to estimate the corrosion rate for each type of structural member. The theoretical prediction of these corrosion rates has been attempted, but is no easy task. An easier alternative is to base the rate prediction on the statistical analysis of past data for comparable situations. There are four corrosion-related questions that ideally need to

Box girder ultimate strength modeling

The development of a simple formula for the prediction of box girder ultimate strength is possible using at least three approaches, and it can also be applied to estimates of the ultimate moment of box girders.

The first is an analytical approach that is based on an assumed stress distribution over the box section, from which the box’s moment of resistance is theoretically calculated by taking into account buckling in the compression flange and yielding in the tension flange. The second is an

Load modeling

Two load components are considered: dead load and live load (truck traffic).

Uncertainty assessment and reliability calculation

The aim is to calculate the probability of failure, and hence its complement and reliability, related to the ultimate strength of a box girder bridge acted upon by an extreme total bending moment during its lifetime. Box girder strength will reduce with time because of corrosion. Thus, the reliability measure will also reduce with time. As the theory of reliability analysis is discussed in many studies (e.g. [25], [32], [33], [34]), only a very brief description is given here. The probability

Application example

To demonstrate the application of the proposed procedure, a hypothetical steel-box girder bridge is selected from an extensive parametric study aimed at the design of box girder bridge components.

It is assumed that the bridge is not protected against corrosion. It has a simple span of 20 m and two lanes with traffic in the same direction. The cross-section is shown in Fig. 7, Fig. 8. The material and corrosion parameters are assumed to be log-normally distributed; the mean values and standard

Approaches for establishing an acceptance level

To determine the latest time to repair intervention for the girders, it was necessary to establish an acceptance level of reliability below which they may be considered unsafe. In general, most structural failures are caused by human factors, such as errors in design and construction, rather than structural inadequacy or overloading. However, calculation of the probability of failure does not take human factors into account because it is not possible at present to model such factors in the same

Concluding remarks

A probability-based procedure is developed here for the selection of the critical time at which bridge girders should be repaired during their service life. Reliability indices are calculated using available load and resistance models. A probabilistic ultimate strength model was developed in this paper employing the simple analytical formulation derived by Paik and Mansour [21]. Bridge girders are subject to a loss in capacity with time due to corrosion. The live load can be distributed to

Acknowledgements

The present study was undertaken jointly with the Lloyd’s Register Educational Trust (LRET) Research Centre of Excellence at Pusan National University, Korea. The LRET is an independent charity working to achieve advances in transportation, science, engineering and technology education, training and research worldwide for the benefit of all. The second author is also pleased to acknowledge the following support: The National Research Foundation of Korea (NRF) grant funded by the Korean

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