Extent Of Corrosion Research Articles

Corrosion effects on flexural behaviour of EPS sandwich concrete panels: a study using acoustic emission technique

The experimental research utilized expanded polystyrene (EPS) panels sized at 1300 × 600 × 130 mm (length × width × thickness) and induced with corrosion via an impressed current method. Varied extents of corrosion were applied for 120, 240, 360, and 480 h, resulting in mass loss percentages of 6.67%, 8.41%, 10.76%, and 18.13% of reinforcement in different panels. The flexural testing along with acoustic emission (AE) monitoring were performed for evaluation of EPS panels. Results obtained defend the correlation of AE energy with the load energy in the EPS panels. The AE parameters of rise angle and average frequency assist in distinguishing between tensile and shear crack types. The energy released during tensile crack formation in EPS panels is minimal compared to that during shear crack formation. These findings are a basis for further AE investigations into EPS panels and developing AE sensor-based methods for identifying corrosion-induced degradation in EPS panels within structures.

Corrosion failure analysis of steel tubes operating in mining installations: Metallurgical, chemical and mechanical investigations

AbstractCorrosion of steel tubes represents a major challenge for various industries, leading to significant economic and environmental impacts, such as material losses, operational interruptions and safety risks. This study focuses on the metallurgical, chemical and mechanical characterization of corroded steel tubes operating in mining installations using metallographic analysis, X-ray diffraction (XRD), SEM-EDS studies, chemical analysis and micro-hardness measurements. The results reveal the existence of a considerable extent of corrosion, of which, the main corrosion products are magnetite – 72% and goethite – 18.1 associated with corrosion. The corroded tubes measured 0.128% carbon, against 0.23% in new tubes, indicating a loss in weight and mechanical strength properties. The observed tensile strength for the new tubes was 481 MPa while the same for the corroded tubes was to a large extent lower. Furthermore, metallographic examination indicates that indeed the structure is ferrite pearlite as to the composition. This study indicates that 304 L or 316 L stainless steels may be utilized which have better corrosion-protecting coatings thus prolonging service life and reducing maintenance activities.

Deep Learning-Based Decision Support System for Automatic Detection and Grading of Surface Corrosion on Galvanized Steel Sheets

Corrosion in the sheets produced leads to significant material losses, including the loss of resources, capital, labor, energy and knowledge. Corrosion control is significant for sheets produced and sent to customers in iron and steel factories. Surface corrosion testing of produced sheets and the accurate detection of corrosion levels are of great importance. The corrosion detection process for sheets in steel factories is performed visually with the naked eye. This is a subjective and time-consuming method. Identifying corrosion damage by visual detection and accurately determining the type and extent of corrosion requires expertise. Wrong decisions at this stage lead to losses during the production phase. Therefore, there is a need for systems that can automate this process and make it human-independent. In this study, a decision support system was designed to automatically detect the level of corrosion in galvanized sheets using convolutional neural networks. The average accuracy of the system is 97.5%, the average precision is 0.98, the average recall is 1 and the average F1 score is 0.99. The results we obtained indicate that a successful system has been developed for the detection and determination of corrosion levels. The high performance of the convolutional neural network models used for corrosion detection supports the practical applicability of the developed system. This system will increase the reliability and efficiency of industrial processes by enabling the accurate and automatic classification of corrosion. This system, which meets a significant need in this area for industrial organizations, reduces production costs and also makes the corrosion detection process more consistent and faster.

Corrosion Behavior of Nickel-Titanium Arch Wires Following the Use of Different Mouthwashes: An In Vivo Study.

The aim of this double-blind in vivo study was to compare the extent of corrosion on the surface of nickel-titanium (NiTi) wires in various mouthwashes. A total of 80 patients who received orthodontic treatment with as-received 0.016x0.022 inch NiTi wires were included in the study, and they were split into 4 groups. The first group used 0.05% of (225ppm F-) sodium fluoride (NaF) (Colgate Plax®) containing mouthwash, 21.6% alcohol (Listerine Cool Mint®) containing mouthwash, and 0.2% clorhexidine (CHX) (Klorhex®) containing mouthwash and the control group used drinking water with melt menthol as mouthwash. After 30 days of using mouthwash, the surfaces of NiTi wires were examined with atomic force microscopy (AFM), and surface roughness values were calculated. Mouthwashes containing fluoride, essential oils, and CHX created higher surface roughness on NiTi wires than the control group. The floride-containing mouthwash group showed less corrosion than the CHX group, whereas there was no difference between the essential oil group. AFM images show supportive data with the results of the clinical study. The results were assessed using a 95% confidence interval and a significance level p<0.05. CHX, essential oil, and floride-containing mouthwashes cause corrosion of NiTi wires. Floride-containing mouthwash can be preferred over CHX mouthwash due to its lesser corrosion effect.

Conservation compendium. Part 10: Corrosion of steel frames behind masonry elevations

This article continues from the previous instalment in the series, and aims to guide engineers in assessing the extent of corrosion of steel frames and in selecting appropriate treatment methods.

Experimental Study on the Chlorine-Induced Corrosion and Blister Formation of Steel Pipes Coated with Modified Polyethylene Powder.

In this study, chlorine-induced corrosion and blister formation on steel pipes (SPs) coated with modified polyethylene powder (MPP) were evaluated through various tests, including chlorine exposure, wet immersion, and temperature gradient experiments. The results confirmed that the extent of corrosion and iron leaching varied with the coating type as expected. In batch leaching tests, no corrosion was observed on modified polyethylene-coated steel pipes (MPCSPs) within a chlorine concentration range of 0 mg/L to 10 mg/L; similarly, there were no significant changes in specimen weight or iron levels. In contrast, the control group with uncoated SPs exhibited significant iron leaching and corrosion, a trend consistent in sequential leaching experiments. SEM analysis after a month of chlorine exposure revealed no significant corrosion on MPCSPs, and SEM-EDX confirmed no major changes in the carbon bond structure, indicating resistance to high chlorine concentrations. Comparative analysis of wet immersion and temperature gradient tests between MPCSP and conventional epoxy-coated SP (ECSP) specimens revealed that MPCSPs did not develop blisters even after 100 days of immersion, whereas ECSPs began showing blisters as early as 50 days. In temperature gradient tests, MPCSPs showed no blisters after 100 days, while ECSPs exhibited severe internal coating layer blisters.

Internal pipe corrosion assessment method in water distribution system using ultrasound and convolutional neural networks

Internal pipe corrosion within water distribution systems leads to iron oxide deposits on pipe walls, potentially contaminating the water supply. Consuming iron oxide-contaminated water can cause significant health issues such as gastrointestinal infections, dermatological problems, and lymph node complications. Therefore, non-destructive and continuous monitoring of pipe corrosion is imperative for water sustainability initiatives. This study introduces a dual-mode methodology utilizing advanced ultrasound technology and convolutional neural networks (CNN) to quantify pipe corrosion. Scanning acoustic microscopy (SAM) employs high-frequency ultrasound to generate high-resolution images of pipe thickness, indicating iron oxide accumulation. SAM also captures internal pipe data to measure iron oxide concentration in the water. This data, analyzed by CNN, achieves an impressive 95% accuracy. This dual-mode system effectively assesses both the extent of pipe corrosion and water contamination, exemplifying the successful integration of SAM and CNN for precise and reliable monitoring.

Investigation of Mild Carbon Steel Immersed in Jatropha Biodiesel Fuel: Spectroscopic and Surface Studies

The use of renewable energy fuels in the automobile industry has seen progressive interest and increased research in recent times. Different types of steel alloys have been considered as materials in the construction of the fuel delivery and storage systems of the automobile engines which are conduit for passage of these biofuels to the specific engine combustion chamber. The nature of the interactions between the surface of the mild steel alloy and the specific biodiesel molecules needs to be interrogated to ascertain the extent and degree of biodiesel activity-induced corrosion. In this study, FTIR, UV-Vis spectrometry and optical microscopy techniques were used to elucidate on the biodiesel molecule-mild steel surface interphase interactions. UV-Vis investigation revealed pronounced peaks around 900 nm and 1050 nm consistent with signals due to poly-unsaturated components of the biodiesel. FTIR analysis showed peaks around 1700 cm-1 which indicated the presence of C=O and C-O functional groups that is associated with triglycerides. Peak signals around 2950 cm-1 are attributed to anti-symmetric and symmetric stretching vibration of C-H in CH2 and CH3 while peaks around 1150 cm-1 indicated the stretching vibration of C-O ester. The results revealed jatropha biodiesel-induce corrosion was physically adsorbed on the steel surface leading to surface degradation over time and were evident in the optical surface micrographs which were equally supported by the FTIR and UV-Vis analyses. Thus, carbon steel alloy material selection and testing to ascertain compatibility and effectiveness is vital when biodiesel is to be used as fuel in automobile engines.

Evaluation of Bolt Corrosion Degree Based on Non-Destructive Testing and Neural Network

Anchor bolt corrosion is a complex and dynamic system, and the prediction and identification of its corrosion degree are of significant importance for engineering safety. Currently, non-destructive testing using ultrasonic guided waves can be employed for its detection. Building upon the analysis of anchor bolt corrosion mechanisms, this paper proposes a method for evaluating the corrosion degree of anchor bolts based on multi-scale convolutional neural networks (MS-CNNs) that address the multi-mode propagation and dispersion effects of ultrasonic guided wave signals in non-destructive testing. Electrochemical experiments were conducted to simulate anchor bolt corrosion, and ultrasonic guided wave non-destructive testing was performed every 12 h to obtain waveform data. An MS-CNN was then utilized to accurately diagnose the corrosion degree of the anchor bolts. The test results demonstrate that this method effectively detects and diagnoses the extent of anchor bolt corrosion, facilitating timely troubleshooting and preventing potential safety accidents.

Atmospheric corrosion behavior of ferritic-pearlitic, spheroidized, and bainitic microstructures of a mild steel

The present study investigates the comparative atmospheric corrosion behavior of three microstructural variants of mild steel (MS), namely, ferritic-pearlitic, spheroidized, and bainitic, made by air cooling, air cooling followed by spheroidizing annealing, and austempering, respectively. The samples were kept outdoors for three years for analyzing the extent of atmospheric corrosion. The samples were intermittently removed at 1, 2, 3, 6, 18, 24, and 36 months and corrosion rates were calculated through the weight loss method. The corrosion rates of the steels irrespective of the microstructure were high in the beginning, and later it slowed down due to the formation of stable rust phase, i.e., goethite phase (α-FeOOH). In addition, after three years of exposure, the bainite variant exhibited the lowest corrosion rate. Overall, the initial corrosion rates were found to predominantly depend upon the corrosion damage due to the formation of micro-galvanic couples. However, at the later stage of exposure, the corrosion rates were influenced by the variation of rust phase fractions and their compactness.

Understanding the effect of microstructure and composition on localized corrosion susceptibility of 6xxx aluminum alloys

The corrosion performance of 6xxx series Al alloys has been found to depend on small changes in composition and microstructure. The corrosion behaviors of three aluminum alloys, AA6111, AA6451, and AA6016, were investigated. AA6111, containing primarily α (Al15 (Fe,Mn)3Si2) intermetallic particles (IMPs), and AA6016, containing primarily β (Al8Fe2Si) IMPs, exhibited the best and the worst overall corrosion performances, respectively, as indicated by the extent of corrosion in exposure tests. However, this ranking was not predicted by the standard interpretation of potentiodynamic polarization curves measured on the alloys. The corrosion susceptibilities of the three alloys were further investigated by evaluating the electrochemical behavior of the component phases separately. Bulk analogs of the component phases were fabricated using standard alloy casting techniques. The fabricated bulk analogs of α and β IMPs, as well as the three alloy matrix phases, were tested using either macrocell or microcell testing. An explanation for the alloy performances was developed by combining the behavior of the component phases.

Corrosion characteristics and evaluation of galvanized high-strength steel wire for bridge cables based on 3D laser scanning and image recognition

The study investigates the corrosion behavior of galvanized high-strength steel wire, which significantly affects the bearing capacity and residual fatigue life of cables in cable-supported bridges. Through standardized salt spray accelerated corrosion tests, steel wires with varying corrosion degrees are obtained. Three-dimensional laser scanning technology reconstructs the corroded wire surface, while image recognition techniques extract geometric characteristics of corrosion pits. Fitting expressions are established to correlate the minimum cross-sectional area, maximum pit depth and dip angle, and mass loss ratio of the wire. Statistical analysis reveals log-normal distributions for the lengths of major and minor axes of corrosion pits over time. Fitting curves for elongation after fracture, nominal yield strength, and nominal ultimate strength, along with elastic modulus distribution, are derived for different mass loss ratios. Comparing corrosion grading criteria, the study quantitatively describes corrosion characteristic parameters for distinct corrosion grades. These insights enhance understanding of corrosion behavior and mechanical property degradation in high-strength steel wires, offering a quantitative framework for assessing and classifying corrosion extent based on measurable parameters.

Long-term corrosion of copper alloys in the soil: new aspects of corrosion morphology in archaeological vessels from south-western Iran

A group of copper-based objects excavated at Deh Dumen cemetery, in south-western Iran, was studied and analysed to examine the long-term corrosion morphology and mechanism in the soil burial environment. For this purpose, twenty-two samples from twenty-one copper-based vessels were studied and analysed using X-ray diffraction, scanning electron microscopy—energy dispersive X-ray spectroscopy, micro-Raman spectroscopy and metallography techniques. The results of the analyses showed that the majority of vessels are made of tin bronze, along with two arsenical copper samples. The extent of corrosion observed ranges from very thin corrosion crusts to thick crusts and entirely corroded structures. These three identified corrosion morphologies display a multi-layered corrosion stratigraphy as well as the preserved limit of the original surface. The corrosion crusts include internal tin-rich and external copper-rich layers, and the main corrosion mechanism for the formation of multi-layered corrosion crusts is decuprification or selective dissolution of copper during the long-term burial time in a moderately Cl-contaminated soil. The three identified corrosion morphologies are similar to the previously published morphologies, but some clear deviations are apparent and are discussed here.

Biofouling and corrosion rate of welded Nickel Aluminium Bronze in natural and simulated seawater

Updated understanding on the effect of biofouling on corrosion rate is needed to protect marine structures as climate change is altering seawater physiochemistry and biofouling organism distribution. Multi-disciplinary techniques can improve understanding of biofouling development and associated corrosion rates on metals immersed in natural seawater (NSW). In this study, the development of biofouling and corrosion on welded Nickel Aluminium Bronze (NAB) was investigated through long-term immersion tests in NSW, simulated seawater (SSW) and air. Biofouling was affected by geographic location within the marina and influenced corrosion extent. The corrosion rate of NAB was accelerated in the initial months of exposure in NSW (1.27 mm.yr−1) and then settled to 0.11 mm.yr−1 (annual average). This was significantly higher than the 0.06 mm.yr−1 corrosion rate measured in SSW, which matched published rates. The results suggest that corrosion rates for cast NAB should be revised to take account of biofouling and updated seawater physiochemistry.

Insights into the Corrosion Inhibition Mechanism of Canavalia gladiata Leaf Extract for Copper in Sulfuric Acid Medium.

Canavalia gladiata leaf extract (CGLE) is extracted from crop waste employing a water decoction method. By employing electrochemical techniques, morphology analysis, quantum chemical calculations, and other methods, we extensively investigated the anticorrosion efficacy of CGLE on copper within a H2SO4 solution. The outcomes reveal that at 298 K, a CGLE concentration of 800 mg/L attains a remarkable inhibition efficiency (IE) of 96.8%. Additionally, we examined the impact of CGLE on the corrosion resistance of copper at varying temperatures. Even with rising temperatures, CGLE manages to sustain an IE of over 95%. This indicates that CGLE is mainly chemisorption based on the copper, leading to a strong adsorption. The surface test results show a noteworthy decrease in the extent of copper surface corrosion upon the introduction of CGLE. The study of the adsorption model demonstrates the alignment of CGLE adsorption onto the copper with the Langmuir adsorption.

Industrial scale fouling of heat exchangers in isocyanate production

The fouling of a commercial stainless steel (AISI 316L) during the manufacture of polymeric methylene diphenyl diisocyanate (pMDI) has been studied using laboratory‐based fouling apparatus that simulates commercial production conditions. The goal of the work is to understand the mechanisms behind the corrosion and fouling during isocyanate production with a view to improving process efficiency, not only in this process, but also others using similar plant and processes. Steel coupons were exposed to a solution of pMDI and solid amine hydrochloride, with hydrogen chloride gas being bubbled through the reaction cell. A number of different conditions were investigated, the variables being pMDI concentration, HCl gas flow duration, immersion time and temperature. Following the fouling experiments the coupons were removed from the fouling rig, photographed, and examined by XPS and ToF‐SIMS; principal component analysis was used to extend the ToF‐SIMS analysis to identify organic fouling products. The extent of fouling is shown to be relatively insensitive to pMDI concentration, but significantly influenced by continual HCl flow and increased temperature, features which increase the extent of substrate corrosion thought to be a precursor to the fouling process itself. Both XPS and ToF‐SIMS confirm the formation of various nickel chlorides in the corrosion process. Urea and metal corrosion products are found to co‐exist on certain (random) areas of the coupon surface.

Temperature and Reaction Time’s Effects on N80 Steel Corrosion Behavior in Supercritical CO2 and Formation Water Environments

In the present study, an immersion experiment was carried out to examine how N80 steel corrodes when exposed to formation water containing dissolved CO2 and supercritical CO2 (Sc-CO2) along with water vapor. We employed electrochemical and surface analysis methods to examine the influence of various factors, including the temperature and duration of immersion, on the extent of corrosion. The results show that the corrosion patterns of N80 steel in a supercritical CO2 environment and CO2-saturated formation water differed significantly. The presence of similar corrosion features was suggested by the constant structure of the corrosion products identified in the formation water. However, the morphology of the corrosion product was complex in the supercritical CO2 environment, exhibiting features of pitting and localized corrosion. Furthermore, a non-linear trend in the corrosion rate was observed between 40 °C and 120 °C. Specifically, the rate of corrosion declined from 40 °C to 80 °C, but it then resumed its growth from 80 °C to 120 °C. These findings suggest that very high temperatures could lead to the destruction of corrosion products and subsequently enhance the corrosion process.

Long‐term atmospheric corrosion rates of Zn55Al‐coated steel

AbstractHot‐dip Zn55Al‐coated steel samples have been exposed for up to 6 years at 11 different weathering sites, including marine, marine‐industrial, acid‐rain and dry atmospheres. From the mass loss measurements, Zn55Al metallic coating showed globally long‐term good corrosion resistance in all weathering conditions compared with hot‐dip Zn‐0.2Al‐coated steel (Z). Yet, weaker performance was observed on Zn55Al in high SO2 polluted atmosphere, particularly when combined with seawater aerosols. This is explained by a more acidic surface condition linked to high SO2. Although the extent of corrosion in this phase was different at the different sites, the final corrosion products formed after 6 years were rather similar at all sites. This consists of hydrous aluminium sulphate or hydrous aluminium hydroxy sulphate and, probably also a smaller amount of sulphate‐containing zinc corrosion products or Al/Zn products.

Application of Nano Material (ZrO2) In Corrosion Resistance of Rebar

For the attainment of least amount of rate of corrosion, different percentages of nano particle ZrO2 is added to epoxy to give a neat coating. The optimum dosage of ZrO2 is found out in order to control the rate of corrosion of rebar embedded in concrete. The composite coated, i.e, nanoZrO2 and epoxy coated specimens are placed in alkaline medium, namely 5% NaCl solution. The rate of corrosion readings were noted down using the reference electrode (calomel) and voltmeter. The rate of flow of current is proportional to rate of corrosion. The readings were noted down over a period of time; 0th day, 1st week, 2nd week, 3rd week and 4th week ; to have a clear idea about the extent of corrosion taking place in the alkaline medium. The optimum percentage of nanoZrO2 to be was found out to be 2%. The test also comprise of evaluating the bond strength between the rebar’s and concrete with that of control specimen.

Understanding and Modeling the Stochastic Nature of Corrosion Reactions in Atmospheric Conditions

Corrosion is a detrimental materials degradation mechanism to many in-service alloys and alloy systems. The stochastic nature of corrosion processes makes prediction and identification of degradation a monumental task. Additionally, the wide range of materials utilized in complex systems, coupled with variable environments, further complicates this process. Here, we utilize Finite Element Method (FEM) models coupled with statistical software (Dakota), and machine learning techniques to build a generalized framework to evaluate the probability of corrosion occurring. The ability to input defined, statistically distributed model parameters allows for the identification of corrosion probability and provides for the discovery of important parameters for future experimental efforts. In addition to the statistical predictions of corrosion, machine learning (ML) techniques allow for accelerated predictions from models, potentially reducing both time and computation effort for corrosion predictions (i.e., rate and extent of corrosion). The framework for corrosion modeling will be discussed and applied to various models, including reactive transport models. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. This document is SAND2023-02444C.