Modeling Of Pitting Corrosion Research Articles

Cellular Automata Simulation of Pitting Corrosion of Stainless Steel in Marine Environments

Pitting corrosion poses a significant hidden risk to the reliable operation of stainless steel equipment. In this study, the evolution of pitting corrosion in stainless steel in marine environments was simulated by developing two-dimensional cellular automata (CA). The model demonstrated its capability to generate corrosion sectional views and top views that were consistent with experimental results. The simulation results obtained from the CA pitting corrosion model converged with the experimental data, yielding minimal errors of 4%. This convergence substantiated the effective ability of the model to simulate pitting corrosion evolution. When the CA model was used to predict pitting development in stainless steel, the obtained predicted values aligned within a 10% margin of error compared with experimental values. The developed CA model was used as a foundation to investigate the effect of chloride ion concentration on both pitting rate and pit morphology. The result showed that the impact of chloride ions concentration on pitting growth was more significant when concentrations were below 3.5wt.%. The establishment of the CA model makes it possible to simulate and predict pitting development patterns, thereby providing guidance for ensuring the safe operation of marine equipment.

Effect of Cerium on Inclusion Evolution and Pitting Corrosion of Nb-Microalloyed Steel.

Nb-microalloyed steels are widely used in construction engineering fields due to their excellent mechanical properties, but they face serious corrosion problems in service environments. Pitting corrosion is the severest form of corrosion, and the types of inclusions are the leading cause to induce pitting corrosion. A new strategy is proposed to enhance the corrosion resistance of steels by achieving a beneficial transformation of inclusions with Ce treatment. In this paper, two types of Nb-microalloyed steels (0% Ce and 0.0058% Ce steel) were prepared to study the modification effect on inclusions in industrial production. The spherical CaS•C12A7 inclusions were modified to smaller ellipsoidal Ce2O2S inclusions, and the proportion of inclusions (0-2 μm) increased significantly from 27 to 66%, while large inclusions (>6 μm) disappeared. A kinetic model of inclusion evolution was established. The results of electrochemical tests indicated that the corrosion potential was positively shifted, and the corrosion current was reduced after Ce treatment. Additionally, the number of defects in the passivation film was decreased, and the corrosion resistance of the steel was significantly improved. The addition of Ce changed the types of inclusions and reduced the number of pitting nucleation points, which led to a remarkable reduction in the number and size of pitting pits. The mechanism of pitting corrosion induced by different types of inclusions was further investigated, and a pitting corrosion model was modeled based on the immersion experiments. Research results provide theoretical support for enhancing the corrosion resistance of steel.

A Convolutional Neural Network-Based Corrosion Damage Determination Method for Localized Random Pitting Steel Columns

As one of the most common forms of corrosion in the marine environment, pitting corrosion can have a detrimental impact on the ultimate strength of steel columns. Pitting pits are usually covered by corrosion products, and the detection of pitting is very difficult, so how to effectively identify random pitting corrosion on steel columns has become a very vital issue. In this paper, a deep-learning-based pitting damage determination method for steel columns is investigated by combining numerical simulation and theoretical analysis, which was validated by experimental results. First, a multi-parameter localized pitting corrosion model was proposed that considered the pitting corrosion randomness in time and space distribution. Second, the relationship between the ultimate strength and corrosion rate of steel columns was analyzed. Finally, a steel column damage determination framework was constructed based on the convolutional neural network. Results showed that the ultimate strength and corrosion rate developed different trends in various corrosion regions, and a damage determination accuracy of 90.2% could be achieved by the neural network after training, which satisfied the practical engineering requirements. This study lays the groundwork for further application of deep learning to the research on the pitting damage to steel structures.

Phase-field modeling of pitting and mechanically-assisted corrosion of Mg alloys for biomedical applications.

A phase-field model is developed to simulate the corrosion of Mg alloys in body fluids. The model incorporates both Mg dissolution and the transport of Mg ions in solution, naturally predicting the transition from activation-controlled to diffusion-controlled bio-corrosion. In addition to uniform corrosion, the presented framework captures pitting corrosion and accounts for the synergistic effect of aggressive environments and mechanical loading in accelerating corrosion kinetics. The model applies to arbitrary 2D and 3D geometries with no special treatment for the evolution of the corrosion front, which is described using a diffuse interface approach. Experiments are conducted to validate the model and a good agreement is attained against in vitro measurements on Mg wires. The potential of the model to capture mechano-chemical effects during corrosion is demonstrated in case studies considering Mg wires in tension and bioabsorbable coronary Mg stents subjected to mechanical loading. The proposed methodology can be used to assess the in vitro and in vivo service life of Mg-based biomedical devices and optimize the design taking into account the effect of mechanical deformation on the corrosion rate. The model has the potential to advocate further development of Mg alloys as a biodegradable implant material for biomedical applications. STATEMENT OF SIGNIFICANCE: A physically-based model is developed to simulate the corrosion of bioabsorbable metals in environments that resemble biological fluids. The model captures pitting corrosion and incorporates the role of mechanical fields in enhancing the corrosion of bioabsorbable metals. Model predictions are validated against dedicated in vitro corrosion experiments on Mg wires. The potential of the model to capture mechano-chemical effects is demonstrated in representative examples. The simulations show that the presence of mechanical fields leads to the formation of cracks accelerating the failure of Mg wires, whereas pitting severely compromises the structural integrity of coronary Mg stents. This work extends phase-field modeling to bioengineering and provides a mechanistic tool for assessing the service life of bioabsorbable metallic biomedical devices.

Time-dependent multi-hazard seismic vulnerability and risk assessment of deteriorating reinforced concrete bridges considering climate change

Climate change inevitably affects the deterioration of reinforced concrete (RC) bridges exposed to harsh chloride environments. This deterioration reduces the resistance of RC bridges to natural hazards, including earthquakes and floods. This paper proposes an improved framework for time-dependent multi-hazard seismic vulnerability and risk assessment of a deteriorating RC bridge considering climate change. The framework addresses (a) the corrosion initiation and propagation processes affected by climate change, (b) time-dependent corrosion rate, (c) seismic fragility analysis of a deteriorating RC bridge using a three-dimensional finite-element model, and (d) the integration of deterioration due to corrosion, climate change, and earthquake and flood-induced scour hazards into time-dependent seismic vulnerability and risk assessment. This paper provides extensive comparisons to demonstrate the effects of corrosion propagation based on uniform and pitting corrosion models, climate change, intensity of ground motion of earthquakes, and flood-induced scour on seismic vulnerability and risk. For illustration, an existing multi-span RC girder bridge is investigated. The results show that pitting corrosion under climate change with flood-induced scour significantly increases the seismic vulnerability and risk of deteriorating RC bridges.

B-value definition in Galvele’s pit model

We use one-dimensional mass transport models to investigate the chloride concentration effect on the potential drop inside a pit cavity. Galvele’s pitting model predicts a B value of 59 mV, independent of the complexation reactions and concentration-dependent diffusivity when ions can migrate freely. Higher B values (>59 mV) at 25 °C are commonly attributed to ion interactions in the pit solution, also explaining the material and electrolyte effect on the B value in Galvele’s pit model. Our analysis suggests that practical pitting corrosion models require a comprehensive mass transport component that includes multi-species interactions.

Experimental Characterization and Numerical Modeling of the Corrosion Effect on the Mechanical Properties of the Biodegradable Magnesium Alloy WE43 for Orthopedic Applications.

Computational modeling plays an important role in the design of orthopedic implants. In the case of biodegradable magnesium alloys, a modeling approach is required to predict the effects of degradation on the implant’s capacity to provide the desired stabilization of fractured bones. In the present work, a numerical corrosion model is implemented to predict the effects of biodegradation on the structural integrity of temporary trauma implants. A non-local average pitting corrosion model is calibrated based on experimental data collected from in vitro degradation experiments and mechanical testing of magnesium WE43 alloy specimens at different degradation stages. The localized corrosion (pitting) model was implemented by developing a user material subroutine (VUMAT) with the program Abaqus®/Explicit. In order to accurately capture both the linear mechanical reduction in specimen resistance, as well as the non-linear corrosion behavior of magnesium WE43 observed experimentally, the corrosion model was extended by employing a variable corrosion kinetic parameter, which is time-dependent. The corrosion model was applied to a validated case study involving the pull-out test of orthopedic screws and was able to capture the expected loss of screw pull-out force due to corrosion. The proposed numerical model proved to be an efficient tool in the evaluation of the structural integrity of biodegradable magnesium alloys and bone-implant assembly and can be used in future works in the design optimization and pre-validation of orthopedic implants.

Sampling-based seismic reliability analysis of the corroded reinforced concrete bridge bent

This study presents a sampling-based reliability sensitivity analysis to identify the random variables that are most influential on the seismic reliability of a corroded reinforced concrete (RC) bridge bent. To this end, a nonlinear finite element (FE) model of a scaled RC bent is developed, which accounts for the corrosion initiation and pitting corrosion models, as well impact of corrosion on the cover concrete, core concrete, reinforcing bars, and bond-slip behavior considering underlying uncertainties. Ground motion records are selected using conditional spectrum (CS) method. Pushover analysis is conducted on RC bent in discrete time points to evaluate the corrosion-dependent drift limit for different damage states. Seismic reliability analysis of the RC bent is conducted using Monte Carlo sampling (MCS) method in different damage states and time points. Results indicate the severe decrease in the seismic reliability index of the RC bent after 30 years of exposure to chloride, especially in the higher damage states. Finally, importance vectors are developed based on sensitivity analyses. The obtained results demonstrate that the importance of underlying random variables depends on the corrosion level and intended damage state. The obtained importance vectors show that the random variable related to the seismic input is the most influential variable on the seismic reliability of the corroded RC bent. It is also found that variables related to corrosion initiation time contribute the most to the seismic reliability of the RC bent in the first 15 years, while in the last 15 years the structural variables are the important ones.

A Nonlinear Probabilistic Pitting Corrosion Model of Ni-Ti Alloy Immersed in Shallow Seawater.

The degradation of metal materials in a marine environment represents the consequence of the electrochemical corrosion of metals under the influence of the environment. The application of new materials in the maritime industry requires experimental, real-world research on the form of corrosive damage and the intensity of the corrosion. This paper analyses the pitting corrosion of a rod-shaped nickel–titanium (Ni–Ti) alloy that was produced by means of the continuous casting method. In total, three samples were posted in a real seawater environment and analysed after 6, 12, and 18 months. Pits were detected on the Ni–Ti alloy after 18 months of exposure to the marine environment. The database on pitting corrosion was created by measuring depth in mm, which was performed by means of a nonlinear method, and by the generation of an artificial database of a total of 120, gauged in critical pit areas. The data were obtained by the application of a nonlinear model, and under the assumption that corrosion starts after 12 months of exposure in the corrosive marine environment. The EDX analysis of the Ni–Ti alloy composition inside the pits and on the edges of the pits indicated that the corrosion process in the hole of the pit occurs due to the degradation of the Ni.

A Computational Pitting Corrosion Model of Magnesium Alloys.

Controlling the corrosion rate of implants to maintain mechanical properties during tissue healing is significant in developing magnesium alloy implants. In addition to surface treatment and material properties, the study of geometric alteration and mechanical strength are also vital for implant development. In this study, we developed a three-dimensional model for semi-autonomous computational pitting corrosion. It is based on the Monte Carlo method, modeling magnesium alloy implants toward clinical application. The corrosion probability is based on the number of exposed surfaces to saline and the oxidation characteristics of the elements. The computational results are well compared with the experimental measurement using micro-computed tomography (micro-CT) in 500 h. Subsequently, the computational analysis is extended to 3,000 h of corrosion analysis. The 3D model appears promising to assist the development of biodegradable implants.

Durability life prediction of RC piles subjected to localized corrosion in chloride environments

In this study, an analytical model for evaluating the durability life of reinforced concrete (RC) piles subjected to localized corrosion under chloride attack is proposed. The localized corrosion process is divided into three stages, and a predictive method is presented to predict the durability life of the pile by calculating the time of each stage. The time of each stage is determined based on the chloride diffusion model, the pitting corrosion model and the crack propagation model. The effects of the water-cement ratio, concrete cover thickness, pile concrete quality, relative humidity, chloride threshold level, pitting factor, corrosion current density and initial surface chloride ion concentration on the various stages of localized corrosion and the durability life of the pile are investigated. The analysis results show that the effects of the water-cement ratio and concrete cover thickness on the durability life of the pile are the most significant in the corrosion initiation stage. The durability life is increased by a reasonable choice of both concrete water-cement ratio and concrete cover thickness with constant concrete quality. The durability life of the pile increases with increasing concrete cover thickness, concrete quality, chloride threshold value and limit crack width, while it decreases with increasing water-cement ratio, relative humidity, corrosion current density and initial surface chloride concentration. The influence of the pitting factor is minimal and is mainly in the pit nucleation stage.

Temporal and spatial variability of corrosion of high-strength steel wires within a bridge stay cable

The temporal and spatial corrosion variability of high-strength steel wires has a significant influence on the service performance deterioration behaviors of bridge stay cable. To proposed quantitative descriptions of the temporal and spatial variability, three different kinds of specimens are manufactured by Galvanized steel wires, and the accelerated corrosion experiments are conducted. For the single-wire specimens, the uniform corrosion process, the variation of surface microtopography and the time-dependent pitting corrosion model are investigated. In addition, the spatial corrosion variability of wires within a cable cross section is investigated by considering different damage conditions of sheath. It is found that the uniform corrosion process of the single-wire specimen can be divided into two stages, which correspond to the corrosion of Galvanized coating and substrate, respectively. The variability of uniform corrosion depth decreases firstly and then tends to be steady. The microtopography of corroded wire surface tends from compact spherical structure to be porous, hollow and loose. In the second corrosion stage, the corrosion products seem to be small clumps fluffy or flowery floccule, and then tend to be lamellar cross form and sand granular. The block maximum pitting factor of a single wire can be described by Gumbel distribution, and in the developed time-dependent model, both the location parameter and scale parameter decrease exponentially in the first corrosion stage and linearly in the second corrosion stage. The corrosion process difference factor of wires in adjacent layers of stay cable can be described by Normal distribution when the sheath is globally aging, and the mean value and coefficient of variation are 0.6758 and 0.2543, respectively. The spatial corrosion variability of cable wires is significantly affected by the broken shape of sheath. The difference of global corrosion degree of wires in different layers decreases with the extension of the exposure period. The sheath with rectangular broken shape and quadrate broken shape will lead to stronger spatial corrosion variability in cable wires than that with semi-annular broken shape.

Seismic fragility of reinforced concrete bridge columns utilizing ductile fiber-reinforced concrete covers

The seismic resistance of reinforced concrete (RC) bridge piers reduces over time due to gradual deterioration processes, such as reinforcement corrosion. Using a ductile fiber reinforced concrete (FRC) reinforcement cover may mitigate deterioration. However, current methodologies for estimating deterioration and capacity reduction cannot be applied to bridge piers with cover made of a ductile FRC that behaves differently from conventional concrete. This article utilizes a systematic framework that combines corrosion and seismic analyses to address this limitation. The seismic fragility of an example bridge column with a ductile FRC cover was estimated using the framework and compared to that of a column with a conventional concrete cover. A detailed pitting corrosion model, which explicitly accounted for differences in cover crack patterns of concrete and a ductile FRC, was developed to estimate the rebar mass loss as a function of time. Seismic fragility functions were constructed by nonlinear response history analyses, incorporating rebar mass loss, at discrete times during the life span of the bridge. The results indicate that improved durability of the RC bridge pier enabled by FRC cover translates into a lower probability of seismic damage over time compared to the pier with a conventional concrete cover.

Computational Modeling of the Corrosion Process and Mechanical Performance of Biodegradable Stent

Magnesium alloy stents have drawn increasing research interest in recent years owing to their biodegradable behaviors. As dissolved by corrosion, mass of the magnesium alloy stents decreases with time, allowing mechanical load to gradually transfer to the surrounding tissues. This work aimed to develop a numerical model based on Continuum Damage Mechanics (CDM) combining pitting corrosion and stress corrosion crack to better predict the degradation behavior of biodegradable magnesium alloy stent. It was applied in coronary stents through finite element method compared with the use of single pitting corrosion model. The results indicated that addition of stress corrosion attack accelerated the degradation rate and support performance loss of stent compared with single pitting corrosion. The proposed model would bring new sights to simulation and serve the design of magnesium alloy stents.

Temporal analysis of the performance of an elevated concrete tank considering the corrosion of the steel reinforcement

Reinforced concrete water storage tanks are civil engineering structures subject to very aggressive atmospheric conditions that expose them to harmful corrosion risk. This dangerous phenomenon caused by the penetration of chloride ions causes pitting corrosion and leads to the reduction of the section of the reinforcements and consequently to the loss of strength and the structure performance. In this study, we are interested in analyzing the performance of an elevated storage tank, taking into account the corrosion of the reinforcements subjected to tensile stress, by considering environments with different rates of aggressiveness. A method based on Housner's model is used to evaluate the tension stresses in the reinforced concrete (RC) pedestal (supporting system) of the tank, subjected to the seismic actions. A pitting corrosion model is developed in order to determine the evolution in time of the reinforcements section in different environments. Several parameters influencing corrosion are taken into account, such as concrete cover and the concentration of chlorides ions.

Progressive Collapse Analysis of an FPSO Vessel Hull Girder Under Vertical Bending Considering Different Corrosion Models

Nowadays, with the increasing operational life of ships, the aging effects on their structural behavior need to be investigated precisely. With the corrosive marine environment taken into consideration, one of the important effects of aging that must be studied is thickness degradation. In this paper, with the use of previously proposed equivalent thickness formulations for corroded plates, the progressive collapse analysis software HULLST is enhanced, and then, the effects of different corrosion models of uniform, random, pitting, and tanker pattern types on the ultimate and residual strengths of a floating production, storage, and offloading vessel hull girder are evaluated for the ages of 0 to 25 years. Results reveal that the uniform corrosion and random corrosion models have close outcomes. The value of relative reduction in the ultimate strength of ship hull girder (compared with the intact condition) ranges roughly from 6% for the age of 5 years to 17% for the age of 25 years in the hogging mode. The relative reduction in the ultimate strength ranges from 4% to 16% in the sagging mode. Pitting corrosion and tanker pattern (random) corrosion models lead to higher relative reductions in ultimate strength. The pitting corrosion model leads to a 16%–32% relative reduction in the ultimate strength for the ages of 5–25 years of the ship in either hogging or sagging. The tanker pattern (random) corrosion model leads to a 6%–37% relative reduction in the ultimate strength in the hogging mode and 3%–31% in the sagging mode at ship ages of 5 to 25 years.

Mechanical and Corrosion Testing of Magnesium WE43 Specimens for Pitting Corrosion Model Calibration

Computational modeling can play an important role in the analysis, design, and development of complex medical devices such as biodegradable coronary stents. In this study, experimental mechanical and corrosion testing is conducted to characterize the mechanical and corrosion behavior of magnesium WE43 alloy, a candidate base material for biodegradable magnesium alloy stents. Previously developed uniform and pitting corrosion models are calibrated based on in vitro mechanical and corrosion testing of magnesium WE43 alloy specimens. The calibrated pitting corrosion model can capture the mechanical and corrosion behavior of magnesium WE43, including the experimentally observed non‐linear reduction in failure strength with mass loss, whereas the uniform corrosion model is incapable of capturing this trend. The calibrated corrosion models will be used in future research on magnesium alloy stents.

Seismic life-cycle cost analysis of ageing highway bridges under chloride exposure conditions: modelling and recommendations

Chloride-induced corrosion of highway bridges constitutes a critical form of environmental deterioration and may result in significant escalation of seismic life-cycle costs due to increased fragility during earthquake events. Most of existing literature tends to adopt simplistic uniform area loss assumptions in lieu of potentially complex, yet realistic and more detrimental, pitting corrosion models for seismic vulnerability analysis. Since the degree of deterioration depends on the severity and duration of exposure, there exists a need to investigate the influence of uniform vs. pitting corrosion assumption on seismic life-cycle costs for varied chloride exposure conditions. A case-study example of a highway bridge in Central and Southeastern US reveals consideration of pitting corrosion as critical for extreme exposures compared to relatively minor settings. Subsequently this study provides recommendations to aid bridge engineers and stakeholders to balance between computational cost and accuracy of results to aid prompt decisions on rehabilitation of ageing bridges in different exposure conditions. A framework is also included to compute seismic life-cycle costs from generic measures of corrosion, independent of assumed exposure scenario. This framework is particularly helpful for seismic loss assessment of highway bridges in chloride exposure zones with periodic field measurements to estimate the extent of structural deterioration.

Multi-state Markov modeling of pitting corrosion in stainless steel exposed to chloride-containing environment

Although stainless steels (SSs) have excellent general corrosion resistance, they are nevertheless susceptible to pitting corrosion. The variation of pit depth and density is significant for the prediction of likelihood of corrosion damage occurring in service. Among the available pitting corrosion models, it is difficult to identify a specific model capable of characterizing all the pit formation processes observed and one that can be used for estimating the evolution of pit density distribution with time. A physics-based multi-state Markov model giving a full description of pitting corrosion states is presented. The transition rates used in the model are determined by fitting the model to experimental data. The variation of pit depth and density is simulated. The simulation is verified by experimental scenarios of SS exposed to chloride-containing environments.

Influence of Acetic Acid on Top Localized Corrosion of X70 Steel Pipeline in CO2 Containing Wet Gas

The electrochemical corrosion behavior of X70 steel in CO2 saturated solution with vari- ous concentrations of acetic acid was studied by means of potentiodynamic polarization measure- ment and EIS. Whilst the influence of acetic acid on the top localized corrosion (TLC) of X70 steel pipelines was examined in a set of high temperature and high pressure autoclave. The results showed that in the CO2 saturated solution, the X70 steel was inactive state. While the free corrosion potential of X70 steel shifted positively and its corrosion current density increased with the increas- ing concentration of acetic acid, which may be related to the rising H + concentration, so that the ca- thodic reaction was promoted. In addition, because of the presence of acetic acid, the corrosion scale become loose and easy to detach from the substrate. Finally a pitting corrosion model was proposed to describe the initiation and evolution of the pitting process.