Chloride threshold level for corrosion of steel in concrete

The steel rebar inside reinforce concrete structures is susceptible to corrosion when permeation of chloride from deicing salts or seawater results in the chloride content at the surface of the steel exceeding a chloride threshold level (CTL). The CTL is an important influence on the service life of concrete structures exposed to chloride environments. The present study discusses the state of art on the CTL for steel corrosion in concrete, concerning its measurement, representation, influencing factors and methods to enhance the CTL. As the CTL values reported in the majority of previous studies were varied with experimental conditions, corrosion initiation assessment method, the way in which the CTL was represented, direct comparison between the results from different sets and evaluation was subjected to the difficulty. As a result, total chloride by weight of cement or the ratio of [Cl⁻]:[H⁺] is the best presentation of CTL in that these include the aggressiveness of chlorides (i.e. free and bound chlorides) and inhibitive nature of cement matrix. The key factor on CTL was found to be a physical condition of the steel-concrete interface, in terms of entrapped air void content, which is more dominant in CTL rather than chloride binding, buffering capacity of cement matrix or binders. The measures to raise the CTL values using corrosion inhibitor, coating of steel, and electrochemical treatment are also studied.     

On the penetration of corrosion products from reinforcing steel into concrete due to chloride-induced corrosion

Reinforced concretes were corroded to varying degrees by exposing to cyclic NaCl spray and 40 °C drying. The amount of corrosion products and induced damage were measured using image analysis. We found that corrosion products can accumulate at steel-concrete interface as well as penetrate cement paste and deposit within hydration products, relicts of reacted slag, and air voids. As corrosion increases, the products tend to accumulate at the steel-concrete interface, while the amount penetrating cement paste remains relatively constant. Only a small amount of corrosion is needed to induce visible cover cracking. Implications on modelling time to cover cracking are discussed.     

Inhibitive effect of sodium eperuate on zinc corrosion in alkaline solutions

The effect of sodium eperuate prepared from Wallaba (Eperua falcata Aubl) extract on zinc corrosion was investigated in alkaline solutions with chloride ions (i.e., simulated concrete pore solutions) by using electrochemical techniques. Sodium eperuate inhibits the corrosion of zinc in 0.1 M NaCl solutions with pH 9.6. As its concentration increases to 1 g/L, the inhibition efficiency reaches approximately 92%. In alkaline solutions with pH 12.6, sodium eperuate has no adverse effect on passivity of zinc, and retards the chloride attack. These suggest that sodium eperuate is an effective inhibitor for the protection of zinc in alkaline environments.     

Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion.     

Effect of corrosion severity on fatigue evolution in Al-Zn-Mg-Cu

The effect of existing-localized corrosion on fatigue cracking of 7075-T6511 was established using crack surface marker-band analysis and a fracture mechanics model. The substantial reduction of fatigue life due to EXCO solution L-S surface pre-corrosion is nearly independent of exposure time after initial-sharp degradation, scaling with the evolution of pit-cluster size and initial stress intensity range with exposure time. Independent of exposure time, formation of a resolvable fatigue crack (∼10 μm) accounts for a similar-low (∼5%) fraction of total fatigue life at low stress range (σ_max = 150 MPa, R = 0.1). Crack formation occurs at microscopic protrusions into the corroded volume. A corrosion-modified-equivalent initial flaw size (CM-EIFS); predicted with the AFGROW tool using measured initial aspect ratio, initiation cycles, and total fatigue life inputs; accurately represents the corrosion damage effect on fatigue for a range of exposures. The similar deleterious effect of several corroding environments for various-exposed surfaces is described by a lower-bound CM-EIFS with a 300 μm depth and 1200 μm surface length suggesting fatigue is governed by a microscopic pit-based topography. Either an approximate lower-bound, or specific CM-EIFS calibrated by limited measurements of fatigue life for service-environment exposed specimens, can be used to assess the impact of corrosion in a damage tolerant framework. Complexities (e.g., local H embrittlement, 3D pit geometry, topography dependent initiation, and microstructure sensitive small-crack growth) do not compromise the CM-EIFS estimation, but must be better understood for refined modeling.     

A cellular automaton model for predicting intergranular corrosion

The cellular automata (CA) methodology is applied to the case of intergranular corrosion. Appropriate CA rules are generated which can reproduce and predict the advance of a corrosion front. The proposed model shows qualitative and quantitative agreement with experimental intergranular corrosion data obtained from an aluminium AA2024 alloy in chloride solutions.     

Corrosion rate prediction of 3C steel under different seawater environment by using support vector regression

The support vector regression (SVR) approach combined with particle swarm optimization (PSO) for its parameter optimization is proposed to establish a model for prediction of the corrosion rate of 3C steel under five different seawater environment factors, including temperature, dissolved oxygen, salinity, pH value and oxidation-reduction potential. The prediction results strongly support that the generalization ability of SVR model consistently surpasses that of back-propagation neural network (BPNN) by applying identical training and test samples. The absolute percentage error (APE) of 80.43% test samples out of 46 samples does not exceed 1% such that the best prediction result was provided by leave-one-out cross validation (LOOCV) test of SVR. These suggest that SVR may be a promising and practical methodology to conduct a real-time corrosion tracking of steel surrounded by complicated and changeable seawater.     

Steel corrosion behaviour in carbonated alkali-activated slag concrete

Steel bars embedded in an alkali-activated slag (AAS) concrete were exposed (after curing for 28 days) to an accelerated carbonation test (3% CO₂, 65% relative humidity (RH), and 25 °C temperature) and a laboratory environment (0.03% CO₂, 65% RH, and 25 °C). Ordinary Portland cement (OPC) was also tested for comparative purposes and exposed to identical experimental conditions. The corrosion behaviour of uncarbonated and carbonated AAS and OPC concretes was tested for different times, performing corrosion potential, linear polarization resistance, and electrochemical impedance spectroscopy measurements. Corrosion products were analysed using the Mössbauer technique. The main corrosion products found were magnetite (Fe₃O₄), wüstite (FeO), and goethite (α-FeOOH).     

Influence of geometry on galvanic corrosion of AZ91D coupled to steel

The influence of geometric factors on the galvanic current density distribution for AZ91D coupled to steel was investigated using experimental measurements and a BEM model. The geometric factors were area ratio of anode/cathode, insulation distance between anode and cathode, depth of solution film covering the galvanic couple and the manner of interaction caused by two independent interacting galvanic couples. The galvanic current density distribution calculated from the BEM model was in good agreement with the experimental measurements. The galvanic current density distribution caused by the interaction of two independent galvanic couples can be reasonably predicted as the linear addition of the galvanic current density caused by each individual galvanic couple.     

Assessing corrosion risk in reinforced concrete using wavelets

Corrosion potential measurements were analyzed using the continuous wavelet transform (CWT). The corrosion potentials estimate the probability of corrosion of steel embedded in concrete. The CWT of the corrosion potential data estimates the behaviour in time of the energy distribution associated with the corrosion process. The results obtained indicate that CWT-based ratios can be successfully applied to better understand the different processes involved in the corrosion phenomenon, such as the cracking of concrete.     

Quantum chemical study of some cyclic nitrogen compounds as corrosion inhibitors of steel in NaCl media

Corrosion inhibition efficiencies of 3-amino-1,2,4-triazole (3-ATA), 2-amino-1,3,4-thiadiazole (2-ATDA), 5-(p-tolyl)-1,3,4-triazole (TTA), 3-amino-5-methylmercapto-1,2,4-triazole (3-AMTA) and 2-aminobenzimidazole (2-ABA) as corrosion inhibitors on steel in sodium chloride media were investigated by using semiempirical PM3 and density functional theory (DFT) methods. Quantum chemical parameters such as highest occupied molecular orbital energy (E_HOMO), lowest unoccupied molecular orbital energy (E_LUMO), energy gap (ΔE) and dipole moment (μ) have been calculated for these compounds by using semiempirical PM3 and 6-31G(d), 6-311G(d,p) DFT methods. It was found that theoretical data support the experimental results.     

Probability distribution of pitting corrosion depth and rate in underground pipelines: A Monte Carlo study

The probability distributions of external-corrosion pit depth and pit growth rate were investigated in underground pipelines using Monte Carlo simulations. The study combines a predictive pit growth model developed by the authors with the observed distributions of the model variables in a range of soils. Depending on the pipeline age, any of the three maximal extreme value distributions, i.e. Weibull, Fréchet or Gumbel, can arise as the best fit to the pitting depth and rate data. The Fréchet distribution best fits the corrosion data for long exposure periods. This can be explained by considering the long-term stabilization of the diffusion-controlled pit growth. The findings of the study provide reliability analysts with accurate information regarding the stochastic characteristics of the pitting damage in underground pipelines.     

Damage analysis and cracking model of reinforced concrete structures with rebar corrosion

The damage of concrete cover in reinforced concrete structures induced by reinforcing steel corrosion is investigated in this study. The damage process of the concrete cover can be divided into two distinct stages: the non-cracking stage and the partial cracking stage. An analytical model based on damage mechanics and elastic mechanics is developed to predict the concrete cracking due to steel corrosion. Based on this model, the expansive pressure and the radial loss of steel bar are discussed. Parametric studies are carried out to examine the effects of the correlative factors on the expansive pressure and the steel loss.     

A generic statistical methodology to predict the maximum pit depth of a localized corrosion process

This paper outlines a new methodology to predict accurately the maximum pit depth related to a localized corrosion process. It combines two statistical methods: the Generalized Lambda Distribution (GLD), to determine a model of distribution fitting with the experimental frequency distribution of depths, and the Computer Based Bootstrap Method (CBBM), to generate simulated distributions equivalent to the experimental one. In comparison with conventionally established statistical methods that are restricted to the use of inferred distributions constrained by specific mathematical assumptions, the major advantage of the methodology presented in this paper is that both the GLD and the CBBM enable a statistical treatment of the experimental data without making any preconceived choice neither on the unknown theoretical parent underlying distribution of pit depth which characterizes the global corrosion phenomenon nor on the unknown associated theoretical extreme value distribution which characterizes the deepest pits.Considering an experimental distribution of depths of pits produced on an aluminium sample, estimations of maximum pit depth using a GLD model are compared to similar estimations based on usual Gumbel and Generalized Extreme Value (GEV) methods proposed in the corrosion engineering literature. The GLD approach is shown having smaller bias and dispersion in the estimation of the maximum pit depth than the Gumbel approach both for its realization and mean. This leads to comparing the GLD approach to the GEV one. The former is shown to be relevant and its advantages are discussed compared to previous methods.     

Characterization of steel corrosion in mortar by various electrochemical and physical techniques

In the study characterization of steel corrosion in concrete at the macro- and micro-level was performed. Physical (electrical-resistance probes) and electrochemical techniques (coupled multi-electrode arrays) were implemented in order to upgrade the general information that conventional electrochemical techniques can provide. Measurements were performed in mortar exposed to periodic wetting and drying. Steel corrosion damage was assessed by micro X-ray computer tomography (CT) and SEM. The results were compared and interpreted. By combined use of micro-CT and electrochemical methods, new insights into the corrosion mechanisms of steel in concrete were obtained.     

Operational based corrosion analysis in naval ships

Life extension of ageing steel structures such as naval ships requires consideration of plate thickness losses due to corrosion, particularly when protective measures such as paint coatings and sacrificial protection are not entirely effective. Traditionally, corrosion prediction models for ships take no account of the operational profile. Consequently, the corrosion models have an inherently high variability with poor corrosion prediction capability. A new corrosion model for the prediction of corrosion loss in the seawater ballast tanks of naval vessels has been developed. The model incorporates previously available corrosion models for immersion corrosion and atmospheric corrosion and takes account of operational and environmental variables. Experimental validation is presented for a trial on an operational naval vessel.     

Numerical simulation of the effect of grain size on corrosion processes: Surface roughness oscillation and cluster detachment

This work reports on the numerical simulation results of the grain size effect on the corrosion processes using a cellular automata model. The material considered consists of domains and their edges. The domains represent the monocrystalline cores while their edges represent the intergranular defects. Either a periodic pattern or randomly generated domains of Voronoï tessellation are used. The model parameters, taking into account the polycrystalline aspect of corrosion, are the domain density and the corrosion probabilities of metal grain core and grain boundary sites. The corrosion probability for grain edge is taken as higher than for the grain core. A complicated surface structure appears with a high geometrical roughness if the density of defects is not too high. A strong correlation between the roughness evolution, the metal crystalline properties and the corrosion mechanism of the metal dissolution was established.