Corrosion Level Research Articles

An experimental study into the degradation of elastic, plastic and fracture properties of a pre-corroded ductile material at elevated temperatures

Carbon steel is one of the most commonly used engineering materials. However, the mechanical properties of steel deteriorates due to exposure to harsh environments like corrosive surroundings and high temperatures. Extensive studies have been done to understand the exclusive effect of corrosion and high temperatures on tensile and fracture properties, although their combined effect has not been addressed. The present work aims to experimentally investigate this by conducting tensile and fracture tests at elevated temperatures on pre-corroded ductile steel. Pre-corroded steel was considered with corrosion levels up to 55%. Empirical relationships were established to quantify the degradation in tensile and fracture properties. An unloading compliance approach using a single specimen was utilized to determine the J-integral fracture toughness and also establish traction separation relation for mode I. The results reveal that the combined influence increases the degradation in fracture toughness, but it restricts the degradation in tensile properties.

Experimental behaviour of hybrid carbon steel – stainless steel bolted connections subjected to electrochemical corrosion

To minimise cost in practical applications whilst still obtaining a satisfactory performance, stainless steel is often employed in aggressive marine environments to ensure the durability of the structure, whilst parts of the structure less susceptible to corrosion employ conventional carbon steel. When the two materials are in direct contact in the connection region, galvanic corrosion can occur over time thus leading to an increased level of corrosion of the less noble carbon steel parts and an associated degradation in the structural performance. A comprehensive experimental study on the shear behaviour of hybrid carbon steel – stainless steel bolted connections subjected to electrochemical corrosion is presented in this paper. A total of 30 bolted connection specimens were designed and assembled from hot-rolled carbon steel and stainless steel plates. Two bolt grades, the high strength bolts 10.9 and the precipitation hardening stainless steel bolts 10.9 were used to connect the plates. Employing the electrochemical corrosion method, the specimens were subjected to various levels of corrosion by adjusting the duration over which the specimens were sunk in the corrosive medium, which resulted in both different corrosion morphology as well as different levels of mass loss of the carbon steel plates due to corrosion. The corroded connection specimens were thereafter tested to failure under shear exhibiting 4 different failure modes. The load versus deformation curves were recorded and are reported herein, whilst the observed failure modes were also documented. It was revealed that increased level of corrosions led to decreased levels of bolt pretention forces and ultimate resistances of the connections, albeit the severity of the degradation strongly depended on the adopted joint configuration and resulting failure mode.

Optimized deep learning for steel bridge bolt corrosion detection and classification

Corrosion of steel bridge bolts poses a major threat to structural integrity. As a key component, bridge bolts are susceptible to corrosion and detachment, necessitating close monitoring during maintenance. However, the vast number of corroded bolts presents challenges. Conventional detection relies on subjective visual inspection without unified assessment criteria. Fast and accurate localization and classification of bolt corrosion levels thus became a research priority for bridge maintenance. This study puts forward a new two-stage corrosion detection method, integrating Deep Convolutional Generative Adversarial Network (DCGAN) and improved You Only Look Once version 5 (YOLOv5) networks, which enables rapid categorization of bridge bolts by different corrosion extents, providing an intelligent solution for bridge maintenance. First, in the image preprocessing stage, a DCGAN with least squares loss generates simulated corroded bolt images through adversarial learning to expand the dataset. Second, three corrosion levels are defined based on visual features and percentage of surface rust, with this classification scheme applied in dataset annotation. Finally, the annotated images are input into an enhanced YOLOv5 model named YOLOv5-SE for corrosion identification. To improve accuracy, Squeeze-and-Excitation blocks are added after each residual block in the YOLOv5 backbone. Comparative experiments prove YOLOv5-SE's superior performance over YOLOv5 and other models like Faster R-CNN and VGG16. A pytorch system enables model deployment for corrosion detection. The integration of DCGAN simulation and attention-optimized YOLOv5-SE enables precise classification and localization of corroded bolts. This study represented a significant step towards intelligent upgrades in steel bridge maintenance.

Influence of Organic Coating Thickness on Electrochemical Impedance Spectroscopy Response

Electrochemical Impedance Spectroscopy (EIS) is a non-destructive and powerful technique for characterizing corrosion systems, allowing for the evaluation of surface reaction mechanisms, mass transport, kinetic evolution, and corrosion levels of materials. This study aims to analyze the progression of corrosion using EIS, with a focus on the influence of organic coating thickness. For this purpose, layers of high-purity epoxy paint were applied to carbon steel plates with thicknesses of 50 µm, 80 µm, and 100 µm. During the research, a direct correlation was observed between coating thickness and corrosion resistance, emphasizing the importance of identifying the optimal thickness for each type of coating. Additionally, it was found that thicker coatings may experience electrode penetration due to the tensions generated during deposition, resulting in cracks between the layers, while thinner coatings allow electrolyte penetration as they do not provide adequate protection to the base steel. Therefore, the 80 µm thickness demonstrated greater resistance to corrosion compared to the other tested thicknesses.

Experimental study of corrosion effects on pulling force of hook bars in external beam-column connections

The external beam-column connection in concrete structures is particularly important because it is necessary to secure the reinforcement bars of the beam that are embedded within the column, which are often formed as a 90° hook. The attack of chloride ions is also one of the most dangerous damages that affect constructions and reduce their service life. Hence, it was necessary to study the effect of corrosion resulting from chloride ion attack on the strength of hook bars. To achieve this purpose, 26 specimens were designed with various variables, including the corrosion level of the reinforcement bars, compressive strength of the concrete, specimen loading, and the spacing between the stirrups relative to their diameter (S/D). The specimens were subjected to accelerated corrosion in the laboratory using the current density method by applying 0.35 mA/cm2 for 21 and 58 days. The experimental results showed that corrosion of the reinforcing bar in the joint weakens the mechanical behavior of rebars by reducing their strength and the bond between them and the concrete. The effect of the compressive strength of the concrete, specimen loading, and S\\D on the hook pulling force for corroded and non-corroded specimens has been observed, and they also affected the determination of the level of corrosion. Equations have been proposed to develop Faraday's law and determine the pulling force of a hook bar. The proposed equations yielded results that closely matched those from the experimental test.

Seismic resilience assessment of extended pile shaft supported coastal bridges considering scour and uniform corrosion effects

The resilience-informed assessment for coastal highway bridges exposed to multiple hazards plays a crucial role in the decision-making process for their operation, maintenance, and management during the bridge’s long-term service period. This study performs a seismic resilience assessment for a coastal reinforced concrete (RC) bridge under the combined effects of scour and uniform corrosion. Toward this goal, an extended pile shaft supported coastal RC bridge is taken as the benchmark and fifteen scenarios are generated to cover three regular scour conditions and five different corrosion levels. To inform the bridge management, the probabilistic distribution of the bridge service time corresponding to different corrosion levels is developed. Subsequently, the finite element model (FEM) for each scenario of the benchmark coastal highway RC bridge is developed, involving the soil-pile interaction and considering the uncertainty of structural and geotechnical parameters, as well as earthquake ground motions. The failure mode of the corroded extended pile shaft is identified as a flexural failure by comparing their flexural and shear capacities. Finally, a resilience loss ratio is proposed in this study for the first time to quantify the impacts of corrosion level and scour depth changes on seismic resilience across different ground motion intensities. Results indicate that both the seismic fragility and resilience decrease as the corrosion intensifies over time. Specifically, at a given intensity measure (IM) level, the resilience loss ratio increases as the corrosion level intensifies. For the studied benchmark bridge, the scour significantly increases the structural fundamental period, consequently reducing the curvature demand on the pile shaft. As a result, the scour generally decreases the failure probability and the earthquake-induced functionality loss for the extended pile shaft. As scour depth increases, the resilience loss of the bridge at a given corrosion level decreases.

Energy-efficient biphasic solvents for industrial CO2 capture: Absorption mechanism and stability characteristics

The traditional CO2 capture process represented by monoethanolamine has excessive energy consumption, serious oxidative degradation and metal corrosion, which limits its potential for large-scale industrial applications. This study produced a highly effective biphasic 3-amino-1-propanol (MPA)–polyethylene glycol dimethyl ether (NHD)–H2O absorbent with easy modulation of phase separation and low levels of oxidative degradation and metal corrosion. The principal absorbent was MPA, and NHD served as the phase separation solvent. NHD's solvent effect decreased the energy barrier preventing MPA from forming zwitterions (MPA+COO−) and carbamate, thus promoting chemical absorption. The large polarity difference between the reaction products and NHD triggered phase separation, producing a low-polarity CO2-lean phase and a high-polarity CO2-rich phase; 97.41% of the absorbed CO2 accumulated in 43.7% of the CO2-rich phase solution. The sensible heat and latent heat of the MPA–NHD–H2O absorbent were relatively low because of the low saturation vapor pressure, high vaporization enthalpy, and excellent phase separation performance of NHD. The regeneration energy was as low as 2.66 GJ/t CO2, which was 30% less than that for monoethanolamine. Additionally, the oxidative degradation rate for the proposed absorbent was only 10.7% of that for monoethanolamine. This study provides a theoretical reference for application of the MPA–NHD–H2O biphasic absorbent.

Simulation of the degraded (steel - concrete) bond strength due to corrosion via modeling pull out tests

Steel corrosion is recognised as major degradation factor of structural capacity and durability of reinforced concrete (RC) structures, especially in marine environment. RC structures with corroded reinforcement present reduced performance due to loss of the cross-sectional area of reinforcement, cracks in concrete and loss of bond between steel and the surrounding concrete. In the present study, simulation of the degraded bond strength on corroded RC elements was elaborated developing a three-dimensional (3D) model through finite element analysis (FEA) in ABAQUS, taking into account the recommendations of fib Model Code 2010. As a basis for the model validation, an existing experimental study on the effect of corrosion and stirrups spacing on bond behavior was considered. In the abovementioned study the bond mechanism of two groups of corroded RC specimens in confined (stirrups Φ8/120mm) and unconfined (without stirrups) conditions were examined upon the completion of eccentric pull-out tests. In order to model the complex conditions of the corroded steel-concrete interface, the cohesive behavior was adopted by appropriately modificated parameters, for each corrosion level. The bond-slip curves extracted from the developed model were shown to be in a good agreement with the relevant experimental results. In particular, the bond strength of confined RC specimens deviates at about 10% among the analytical and experimental outcomes, for both uncorroded and corroded conditions up to 8.3% corrosion level. In case of the unconfined specimens, the bond strength prediction was satisfactory up to 5% corrosion level, whereas for greater corrosion level, large deviation was observed. Regarding the prediction of the relative slip between steel and concrete, further investigation is required as the development of slip is influenced by a plethora of factors.

Influence of Xinjiang Saline Soil on Corrosion of X80 Pipeline Steel

A large-scale gas transmission pipeline project will pass through typical saline soil areas in Xinjiang, China, to find out the influence of the saline soil on the long-distance pipeline in this area, this paper investigates the corrosive behavior of X80 pipeline steel embedded in saline soil with multiple corrosion intensities. Firstly, NaCl, Na2SO4, NaHCO3, and deionized water were used to simulate the saline soil with different corrosion intensities, and then the corrosion test of X80 steel was carried out. A scanning electron microscope was used to observe the X80 steel before and after corrosion. Finally, the weight loss method was used to calculate the corrosion rate, and the corrosive behavior of X80 pipeline steel in Xinjiang saline soil environment was analyzed. The results show that: (1) X80 steel is susceptible to pitting corrosion in the saline soil environment; (2) the rate and level of corrosion were mainly related to the content of Cl− and SO4 2−. The greater the content, the stronger the pipeline is corroded; (3) the rate and level of corrosion were positively correlated with the corrosion intensities of saline soils.

Performance Evaluation of Corrosion Inhibitors in Electrochemical Resistance of Steel Reinforcement in Concrete

Reinforced concrete (RC) structures are often used in the construction sector due to their strength and longevity. Corrosion in steel reinforcement can have detrimental effects like surrounding concrete cracks and spalls as the steel rusts and expands. Furthermore, weakening the structure, corrosion might make the steel’s bond with the surrounding concrete less strong and results in expensive repairs, safety risks, or even collapse. Studying steel reinforcement corrosion in concrete is essential for several reasons. Firstly, it enhances our understanding of the mechanisms underlying corrosion and facilitates the development of effective prevention and mitigation strategies includes designing materials with improved corrosion resistance, applying protective coatings, or implementing cathodic protection systems to inhibit corrosion. The present investigation is aimed to assess the damage in RC flexural members at no corrosion level and 10% corrosion level using non-destructive testing (NDT) techniques to capture various aspects of the specimen condition. The research examined the efficacy of several corrosion inhibitors, including Epoxy, Grout, Geopolymer, Red oxide, and polythene cover. The findings revealed that Geopolymer demonstrated superior performance in mitigating corrosion. This effectiveness is attributed to its ability to form an alkaline protective layer around the reinforcing bars, which significantly impedes corrosion processes compared to the other inhibitors assessed.

Analysis of shear resistance of stud connectors under different levels of corrosion

Analysis of shear resistance of stud connectors under different levels of corrosion

Fatigue behavior of high strength steels under various levels of corrosion

Propagation of a short fatigue crack directly from a corrosion pit is investigated within this work. A corroded rectangular specimen subjected to remote tensile cyclic loading is modelled via finite element method. Propagation of the angled crack is then controlled by both loading modes (I + II). A parametric study is performed to estimate the directions of further crack propagation for various geometrical configurations. Corrosion pit size is varied to simulate various levels of corrosion, and the analysis is carried out for a range of crack lengths and different initial crack inclination angles. Assumptions of linear elastic fracture mechanics are accepted, and classical maximum tangential stress criterion is applied to calculate the angles of crack deflection. Results obtained are discussed and are prepared to mutual comparison with observations of decrease of fracture mechanical/fatigue properties on real specimens subjected to relevant experiments.

Chloride-induced concrete deterioration monitoring using advanced ultrasonic pulse wave analysis based on convolutional neural network

This research explores the potential of deep learning techniques, specifically the convolutional neural network (CNN) architecture, for classifying concrete crack levels based on an acceptable threshold of concrete cracking. The classification model utilizes ultrasonic pulse wave data collected from concrete cube specimens before and after undergoing an accelerated corrosion process. A total of 108 concrete specimens, representing three different mix designs, three corrosion levels, and four concrete cover thicknesses, were utilized in this study. The collected data was employed to train CNN models, specifically leveraging the GoogLeNet and SqueezeNet architectures. Various input sampling rates, input lengths, and hyperparameters were explored to determine the optimal training setup, yielding the best prediction performance. The results demonstrate that the optimized models achieve an 84% accuracy in distinguishing cracks below and above the acceptable threshold. Therefore, it can be concluded that the CNN method holds potential for in-situ sensors aimed at monitoring chloride-induced deterioration in concrete structures.

The effects of crystal structure on the chemical durability of yttrium disilicate.

Amorphous, α, β, and γ-phase yttrium disilicate Y2Si2O7 pellets were synthesized by spark plasma sintering, and their chemical durability and degradation mechanisms were investigated via semi-dynamic leaching test in pH = 3 nitric acid at 90 °C. All crystalline phases displayed relatively congruent dissolution with a slight preferential release of Y. The amorphous sample showed clear incongruent dissolution with preferential release of Y, leading to a surface reorganization reaction and the formation of a SiO2 passivation layer 20-25 μm thick on the surface of the sample. This passivation layer led to a continuous decrease in the elemental release rates of the amorphous sample. The γ-phase sample displayed the lowest short-term and long-term leaching rates of Y and Si, followed by the β, α, and then amorphous sample. The crystalline samples showed increasing release rates over time indicating a dissolution-controlled reaction mechanism. Post-leaching microstructural characterization of the β and γ samples revealed variations in the corrosion levels of the surface grains, indicating a dependence on grain orientation.

Resistivity Method Evaluation of Corroded OPS-Concrete

Many reinforced concrete (RC) structures are built around coastal areas or above the sea, which has very high risk of corrosion. Steel reinforcement corrosion in RC structures can cause failure of structural if not taken into account. Therefore, in this research, it is very important how durable oil palm shells (OPS) in corrosive area. One way to determine the durability of concrete without damaging it is to use the non-destructive testing method, which in this research uses the resistivity method. The method can evaluate the durability of concrete due to corrosion in OPS concrete. The effect of the percentage addition of OPS (10%, 20%, 30%, and 40%) and the addition of corrosion level (0.5%, 1%, 1.5%, 2%, 3%, and 4%) were also analysed. The results show that adding an oil palm shell (OPS) and the corrosion rate with natural and impressed current methods reduce the flexural strength of the concrete and the value of the resistivity of the concrete. The results show that adding an oil palm shell (OPS) and the corrosion rate with natural and impressed current methods reduce the flexural strength of the concrete and the value of the resistivity of the concrete. The resistivity value decreases along with the addition of the corrosion rate on each specimen.

Intelligent analysis of corrosion characteristics of steel pipe piles of offshore construction wharfs based on computer vision

The lower part of offshore construction wharfs is mostly a steel structure system composed of steel pipe piles, whose corrosion level directly affects the structural safety performance of steel wharfs in service. The currently common corrosion detection methods can only sample and inspect steel pile after it has been dismantled, making it impractical for in-service monitoring during the operational period of the steel pile. In this paper, a deep learning-based image classification model is first established to recognize the type of corroded area on steel pipe piles. The model achieves a recognition accuracy of 99.14 % in automatically identifying different types of corroded areas, including full immersion zone, tidal range zone, and splash zone. Subsequently, digital image processing technology is utilized to automatically calculate the corroded area of steel pipe piles. The method proposed in this paper can obtain the key information, such as type of corrosion area and area of the steel pipe pile corrosion area, without damaging their structural performance during the service. With this data, the mechanical performance of steel pipe piles can be analyzed, and the structural safety of the in-service steel pipe piles can be determined, thereby ensuring the safety of the construction wharf.

Numerical and experimental investigations on quasi-static component generation of longitudinal wave propagation in isotropic pipes

In this paper, the quasi-static component (QSC) generation of longitudinal waves propagating in an isotropic pipe is investigated numerically and experimentally. The three-dimensional (3D) finite element (FE) simulations are first carried out to gain physical insights into the characteristics of QSC generation from longitudinal wave travelling in an isotropic pipe with weak material nonlinearity. By applying the axial displacement excitation in the FE model, L(0, 1) mode and L(0, 2) mode are excited simultaneously. Then, the generated QSC pulses are extracted using the phase reversal approach for analysis. It is found that the QSC pulses generated by L(0, 2) mode and L(0, 1) mode are L(0, 1) mode. Meanwhile, the shapes of QSC pulses at different locations are extracted and compared. In this study, a data pre-processing method is proposed to handle numerically calculated and subsequent experimentally measured displacement signals, and a nonlinear acoustic parameter is defined to evaluate the incipient damages. After that, an experiment is conducted to measure the QSCs induced by the propagation of longitudinal waves in an aluminum pipe. The experimental results indicate that the propagation of longitudinal waves in the aluminum pipe can induce the QSCs. Different levels of corrosion are created on the surface of the aluminum pipe and are assessed by the generated QSCs. The results show that the nonlinear acoustic parameter has a monotonically increasing trend with the growing severity of corrosion. The QSCs generated by longitudinal wave can be used to detect and evaluate the early-stage surface corrosion in the aluminum pipe.

Application of wavelet transform techniques for corrosion assessment of embedded rebars in RC elements using electromechanical impedance

Corrosion of steel reinforcement embedded in concrete significantly influences the integrity and durability attributes of reinforced concrete structures. Monitoring of the early age corrosion of the reinforcements can contribute to an effective planning of structural maintenance and restoration. This paper demonstrates an innovative approach of monitoring the rate of corrosion (mass loss due to corrosion) of steel bars embedded in concrete by capturing conductance signature using Piezoelectric sensors (PZT) by Electromechanical Impedance Technique. In the recent times Wavelet Transform (WT) based different techniques have been proved to be promising techniques for different structural health monitoring assessment. This study aims to comprehensively use the WT techniques based on EMI signals to assess the corrosion levels in the reinforcement embedded in RC members. Specifically, the study focuses on capturing the progression of corrosion levels using the RMSD index derived from the DWT, CWT and WPT analysis of conductance signatures. WT techniques provides energy values of conductance signatures. Energy level of the signatures decreases with the increase of corrosion levels and deviation of energy level between current and pristine stage is measured using statistical index Root Mean Square Deviation (RMSD). Robust relationship between the RMSD index and the corrosion mass loss ratio through nonlinear curve fitting have been derived and presented using data captured from the 48 specimens of concrete cylinders with embedded reinforcement. At last, the comparison between the actual mass loss ratio and the predicted mass loss ratio derived from these techniques have been made for the validation of the proposed relation of predicted mass loss due to corrosion.

Data-driven prediction method for shear capacity of corroded rectangular reinforced concrete shear walls under varied failure modes

The physical and mechanical properties of rectangular reinforced concrete shear walls (RRCSW) will deteriorate over time due to acidic erosion, causing changes in damage characteristics and a reduction in shear capacity under seismic loading. The aim of this paper is to develop a failure mode-based prediction method for the shear capacity of corroded RRCSW, as the existing formulas for calculating shear strength become invalid in such scenarios. Initially, a total of 2403 RRCSW samples with various corrosion levels and main design parameters were generated and simulated using the authors' previous numerical method to obtain a comprehensive database of shear capacity. Subsequently, an efficient damage mode identification method for RRCSW was established using the Random Forest algorithm, and its accuracy and applicability in identifying damage modes of corroded RRCSW were verified. Finally, the existing calculation formulas for RRCSW in flexure-shear and shear failure modes were selected and modified to consider the corrosion effect based on the shear capacity database. The comparative analysis revealed that the proposed formulas provide accurate predictions of the shear capacity of corroded RRCSW, making the results of this study invaluable for seismic design of new structures and seismic performance evaluation of existing structures.

Biofouling and Corrosion Protection of Aluminum Alloys Through Ultrafast Laser Surface Texturing for Marine Applications

AbstractSurface biofouling, corrosion, and wettability are important parameters to understand and characterize aluminum alloys to prevent the failure in marine environments. Antifouling technologies predominantly encompass chemical and biocidal approaches with negative environmental consequences. Therefore, this study focuses on a new method of producing non‐toxic and effective antifouling and corrosion‐resistant surfaces. In this study, ultrafast laser texturing is used to modify the surface of an aluminum alloy using a femtosecond laser system. Five different unique texture patterns are designed and fabricated using 3 W laser power, 100 kHz pulse repetition rate, and 4 mm s−1 scanning speed in order to make the aluminum surface antifouling and corrosion resistant. The non‐textured sample has a contact angle of 85° while the textured samples have contact angles of up to 157°. The contact angle increased with time up to 90 days of aging. Biofouling assessment is conducted using marine algae Nitzschia ovalis as a marine fouling test organism. A reduction of biofilm coverage of 79% is recorded from the laser‐produced star pattern texture. This study demonstrates that laser‐textured surfaces have the potential to mitigate the formation of biofilms on the surfaces while also providing a mechanism to control the relative level of corrosion.