Keywords: bridge, structural reliability, safety, predictive likelihood, corrosion, traffic.

Considerable research effort has been invested in the development of accurate methodologies to estimate the residual strength of reinforced concrete structures subject to degradation over time [1]. However, reliability calculations require the probability distributions for load as well as resistance. As noted by Melchers [2], prediction of the extremes of traffic loading is a critical area of research since the imposed traffic loads are typically the variables with the greatest uncertainty.

In this paper, a novel approach to the estimation of the reliability of reinforced concrete structures is presented which addresses the variability in the traffic load effects in particular. A recent development in the prediction of extreme bridge traffic load effects using predictive likelihood [3] is applied to estimate the variability in the lifetime maximum load effects. In this approach, the statistical distributions for lifetime maximum load effects are estimated from real traffic data measured using weigh-in-motion (WIM) technology. The distribution of residual strength of reinforced concrete structures subject to corrosion of reinforcement, which is considered to be the predominant causal factor for the premature deterioration of reinforced concrete structures [4], is also found.

In order to compute the residual capacity of the structure, the stochastic variables considered are chemical-corrosion initiation time, the equilibrium and threshold chloride concentrations and the chloride diffusion coefficient, geometrical-concrete cover of reinforcement, initial diameter of reinforcement bars, depth of deck and material-related yield strength of steel and compressive strength of concrete.

The assessment of the statistical distributions for lifetime maximum load effect is based on the data of the existing traffic over the bridge. This data accounts for the important traffic-related variables: gross vehicle weight, axle spacings and weights, traffic composition, flow rates and headway.

The stochastic variables described are combined in order to produce two different statistical distributions, one for resistance and one for loading. The determination of statistical distributions for lifetime maximum load effects, as opposed to "characteristic values" found in most of the design codes, facilitates the inclusion of uncertainty of traffic loading into a reliability framework, for which both resistance and loading have to be treated as stochastic variables. This approach has the potential to improve the accuracy of estimates of remaining life of reinforced concrete structures. It may therefore result in significant savings as unnecessary repair and rehabilitation of existing bridges may be avoided.

1

M.P. Enright, D.M. Frangopol, "Probabilistic analysis of resistance degradation of reinforced concrete beams under corrosion", Engineering Structures, 20(11), 960-971, 1998. doi:10.1016/S0141-0296(97)00190-9

2

R.E. Melchers, "Assesment of existing structures - Approaches and research needs", Journal of Structural Engineering, 127(4), 406-411, 2001. doi:10.1061/(ASCE)0733-9445(2001)127:4(406)

3

C.C. Caprani, "Probabilistic Analysis of Highway Bridge Traffic Loading", Ph.D. Thesis, School of Architecture, Landscape, and Civil Engineering, University College Dublin, Ireland, 2005.

4

J. Broomfield, "Corrosion of steel in concrete, understanding, investigating & repair", E & FN Spon, London, 1997.

purchase the full-text of this paper (price £20)

go to the previous paper
go to the next paper
return to the table of contents
return to the book description
purchase this book (price £120 +P&P)