Technical Papers
Mar 9, 2023

Calibrating a Physics-Based Corrosion Model with Field-Based Bridge Condition Data

Publication: Journal of Bridge Engineering
Volume 28, Issue 5

Abstract

This paper presents a novel method for calibrating a physics-based corrosion prediction model using a deterioration curve derived from field-based bridge condition assessments. The corrosion model used in this study considers inputs such as corrosion rate to predict outputs such as concrete crack width. Deterioration curves that present bridge element condition versus time are converted into crack width versus time using inspection guidance from transportation agencies. Input parameters of the corrosion model are calibrated by matching the crack widths predicted by the corrosion model with those predicted by the deterioration curves. The calibration method is demonstrated for a reinforced concrete bridge column in this article. The corrosion rate before cracking, the pitting factor, and the ratio of corrosion rates at critical crack width and before cracking significantly influenced the model results and were calibrated. Postcalibration input parameter ranges were narrower than but within the ranges reported in the literature. A physics-based corrosion model thus calibrated using field inspection data can potentially improve the predictions of future structural health and aid in asset management.

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Acknowledgments

This research was supported by the Region 2 University Transportation Center, which is funded by the US Department of Transportation. Support was also provided by the Institute of Bridge Engineering at the University at Buffalo, the State University of New York. The opinions, findings, and views expressed in this study are the ones of the authors only and do not necessarily reflect the views, policies, standard specifications, or regulations of the parties acknowledged above. Funding agencies do not assume any liability for the contents or the use thereof.

Notation

The following symbols are used in this paper:
A0
original rebar area (mm2);
A1
area parameter 1 depending on D0, P(t), θ1, and b in the pitting corrosion model (mm2);
A2
area parameter 2 depending on D0, P(t), θ2, and b in the pitting corrosion model (mm2);
A(t)
rebar area at time t (mm2);
b
width of the pit area (mm);
C
thickness of the concrete cover (mm);
Ccrit
critical chloride content (kg/m3);
CCl(x, t)
chloride concentration at spatial coordinate x and time t (kg/m3);
Cs
chloride content on the concrete exterior surface (kg/m3);
D0
original rebar diameter (mm);
DCI
effective chloride diffusion coefficient of concrete (mm2/s);
Ec
elastic modulus of concrete (MPa);
erf(·)
error function (—);
f0
yield strength of noncorroded reinforcement (MPa);
f(t)
effective yield strength of corroded rebar at time t (MPa);
fct
tensile strength of concrete (MPa);
icorr
current density;
K
=ratio of λ(t)afcrack to λ(t)bfcrack (—);
mloss
percent of rebar mass loss (or area loss per unit length) due to corrosion (—);
P(t)
pit depth (mm);
Pcorr
internal pressure caused by rust expansion (MPa);
Qcorr
percent weight loss (or area loss) of rebar (—);
R
pitting factor (—);
r0
radius of the thick-wall cylinder (concrete cover) (mm);
r
distance from the center of the thick-wall model to the interface between the rust and concrete (mm);
ri
radius of rebar (mm);
W(t)
crack width of concrete cover at time t as predicted by the corrosion model (mm);
WLB(t)
lower bound of crack width derived from deterioration curves at time t (mm);
WUB(t)
upper bound of crack width derived from deterioration curves at time t (mm);
Wcri
critical crack width, which is the cover crack width beyond which the corrosion rate is assumed to become constant (mm);
W¯(t)
average crack width derived from deterioration curves at time t (mm);
ΔA(t)
cross-sectional area loss of reinforcement at time t (mm2);
δ0
thickness of the porous zone (mm);
λ(t)corr
corrosion rate, amount of metallic material loss in thickness over a unit time (mm/year);
λ(t)afcrack
corrosion rate at critical crack width (mm/year);
λ(t)bfcrack
corrosion rate before cracking (mm/year);
ν
Poisson’s ratio of concrete (—);
θ1
angle parameter 1 depending on D0, P(t), and b in the pitting corrosion model (—);
θ2
angle parameter 2 depending on D0, P(t), and b in the pitting corrosion model (—); and
σ
circumferential stress caused by rust expansion (MPa).

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Go to Journal of Bridge Engineering
Journal of Bridge Engineering
Volume 28Issue 5May 2023

History

Received: Apr 14, 2022
Accepted: Jan 4, 2023
Published online: Mar 9, 2023
Published in print: May 1, 2023
Discussion open until: Aug 9, 2023

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Authors

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Dept. of Civil, Structural, and Environmental Engineering, Univ. at Buffalo, State Univ. of New York, Buffalo, NY 14260-4300 (corresponding author). ORCID: https://orcid.org/0000-0001-5834-1930. Email: [email protected]
Dept. of Civil, Structural, and Environmental Engineering, Univ. at Buffalo, State Univ. of New York, Buffalo, NY 14260-4300. ORCID: https://orcid.org/0000-0001-6030-8371. Email: [email protected]
Pinar Okumus [email protected]
Dept. of Civil, Structural, and Environmental Engineering, Univ. at Buffalo, State Univ. of New York, Buffalo, NY 14260-4300. Email: [email protected]

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