INFLUENCE OF NaCl DEPOSITION ON ATMOSPHERIC CORROSION OF A3 STEEL IN THE PRESENCE OF SO_2

The regularities of atmospheric corrosion of A3 steel deposited with different amount of NaCl exposed to the air containing 1ppm SO2 at 80%RH and 25℃ were studied in laboratory. NaCl can accelerate the corrosion of A3 steel obviously under such condition. The relationship between the weight loss of A3 steel and the amount of NaCl deposition can be well described by using a quadratic function. Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Scanning electron microscopy and electron dispersion X-ray analysis (SEM/EDAX) were used to characterize the corrosion products. In the absence of NaCl, FeSO4 · xH2O is the dominant corrosion products, while Fe3O4, FeSO4·H2O, β-FeOOH and γ-FeOOH dominate in the presence of NaCl.

Role of CO_2 in the initial stage of atmospheric corrosion of AZ91 magne-sium alloy in the presence of NaCl

The effect of CO2 and NaCl on the initial stage of atmospheric corrosion of AZ91 magnesium alloy was studied. The observation of surface morphology by optical microscopy （OM）, scanning electron microscopy （SEM） and the analysis of corrosion products by X-ray diffraction （XRD） were integrated to investigate corrosion evolution. The results showed that NaCl stimulated the corrosion by promoting the formation of thin electrolyte film, increasing the conductivity and breaking the protective film in the absence of CO2. The morphology of the corroded samples with deposited NaCl was more homogenous in the presence of CO2. It was suggested that NaCl-induced corrosion was inhibited in the presence of CO2 by the formation of slightly soluble corrosion products containing hydroxy carbonates and hydroxy chlorides that provided a partly protective layer on the surface of the magnesium alloy.

Influence of NaCl Deposition on Atmospheric Corrosion of A3 Steel

Regularity of the initial atmospheric corrosion of A3 steel in the presence of NaCI was investigated. The results showed that NaCI can accelerate the corrosion of A3 steel. Dry mass gain of A3 steel in the presence of NaCI deposition increases with the exposure time, which can be correlated by using exponential decay function. The relationship between dry mass gain and amount of NaCI deposition at a certain exposure time follows a quadratic function. More amount of NaCI deposition will slow down the corrosion rate to some extent after exposure for a certain time. SEM/EDAX was used to characterize the corrosion surface and products. The surfaces of the NaCI treated A3 steel were obviously uneven, and some tiny crevices appear in the corrosion products that could help O2 transmit to the inner layer. The amount of oxygen in atomic percentage in the corrosion products increases with the amount of NaCI deposition.

ATMOSPHERIC CORROSION OF 304AND 316 STAINLESS STEELS

Atmospheric corrosion of 304 and 316 stainless steels was studied by field exposure test, in which rain water was collected and analyzed by atomic absorption spectroscope (AAS). Emphasis was put on the dissolution of chromium and nickel from the stainless steels by atmospheric corrosion and rain runoff. AAS analyses shows that the amounts of yearly chromium and nickel dissolution were less than 150ng/cm 2 and 50ng/cm 2 respectively for both 304 and 316 stainless steels. XPS analysis reveals the marked Cr enrichment on the 316 stainless steel after one year field exposure. SEM shows the morphology of corrosion pits on the steel surfaces.

Atmospheric Corrosion of Steel A3 Deposited with Ammonium Sulfate and in the Presence of Sulfur Dioxide

A laboratory study of the atmospheric corrosion of carbon steel deposited with (NH4)2SO4 in the presence of SO2 is reported. The different levels of (NH4)2SO4 (0, 15, 30, 45, 60 μg·cm-2) were added on the surface of the samples before the exposure. The corrosion was investigated by a combination of gravimetry, Fourier transform infrared spectroscope and scanning electron microscopy. A detailed knowledge about the corrosion products was acquired, both quantitatively and qualitatively. The results show that the metal loss increased and the increasing tendency of corrosion rates slowed down with the increasing exposure time. The phase constituents of the corrosion products are mainly α-FeO(OH), γ-FeO(OH), and δ-FeO(OH).

Effect of CO_2 on Atmospheric Corrosion of UNS G10190 Steel under Thin Electrolyte Film

The atmospheric corrosion of UNS G10190 steel under a thin electrolyte film in the atmosphere polluted by CO_2, has been studied in the lab using an atmospheric corrosion monitor (ACM) in combination with XRD and SEM observations of the surface of steel. The ACM study indicated that the corrosion rate of the steel increased with increasing carbon dioxide concentration. The XRD and SEM observations showed that no carbonate was found in the corrosion product on the steel surface. The corrosion product consisted of two layers, i. e., inner and outer layer. From the experimental results, it was concluded that CO_2 played an enhancing role in the atmospheric corrosion of UNS G10190 steel. The film of the corrosion product showed slight protection.

Atmospheric corrosion behavior of Nb-and Sb-added weathering steels exposed to the South China Sea

The atmospheric corrosion behavior of new-type weathering steels(WSs)was comparatively studied,and the effects of Nb and Sb during corrosion were clarified in detail through field exposure and characterization.The results showed that the addition of Nb and Sb played positive roles in corrosion resistance,but there was a clear difference between these two elements.Nb addition slightly improved the rust property of conventional WS but could not inhibit the electrochemical process.In contrast,Sb addition significantly improved the corrosion resistance from the aspects of electrochemistry and rust layer.Compared with only 0.06wt%Nb,the combination of 0.05wt%Sb and 0.06wt%Nb could better optimize the rust structure,accelerate the formation of a high proportion of dense and protectiveα-FeOOH,repel the invasion of Cl^(−),and retard the localized acidification at the bottom of the pit.

Atmospheric Corrosion Monitoring of Field-exposed Q235B and T91 Steels in Zhoushan Offshore Environment Using Electrochemical Probes

This work aimed to in-situ monitor the atmospheric corrosion of steels exposed to Zhoushan offshore environment by using electrochemical noise（EN） technique. A portable EN monitoring system was established and two electrochemical probes（named as Q235 B and T91） were designed. Experimental results indicated that the noise resistance of T91 steel was higher than that of Q235 B steel, revealing that the corrosion resistance of T91 was higher than that of Q235 B. A 60-day monitoring result indicated that the noise resistance was well correlated with the weight loss data. Wavelet analyses results of EN data indicated that Q235 B underwent uniform corrosion and T91 suffered from localized corrosion, which was further confirmed by the surface observation. It is concluded that EN can be used as a new method to identify the corrosion form and corrosion resistance in atmospheric conditions.

Influence of Al Content on the Atmospheric Corrosion Behaviour of Magnesium-Aluminum Alloys

The influence of AI content on the Mg-AI alloys corrosion performance during sodium chloride induced atmospheric corrosion has been studied. It was found that the corrosion rate of three Mg-AI alloys was accelerated with increasing AI content. The poor corrosion resistance was attributed to the galvanic coupling between the phase and eutectic phase or α phase and the formation of porous corrosion products.

INITIAL ATMOSPHERIC CORROSION OF ZINC IN THE PRESENCE OF NH_4Cl

Influence of NH_4 Cl on the initial atmospheric corrosion of zinc was investigated viaquartz crystal microbalance (QCM) in laboratory at 80%RH and 25℃. The resultsshow that NH_4 Cl can accelerate the initial corrosion of zinc. Mass gain increase withthe exposure time, but mass gain in the later doesn't change obviously due to theformation of the insoluble simonkolleite on zinc surface in the presence of NH_4 Cl.Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) wasused to characterize the corrosion products. Zn_5Cl_2(OH)_8·H_2O,(NH_4)_2ZnCl_4 andZnO are the corrosion products on zinc. Brief discussion on the mechanisms of at-mospheric corrosion of zinc in the presence of NH_4 Cl was introduced.

Mechanistic Studies of Atmospheric Corrosion Behavior of Al and Al-based Alloys in a Tropical Marine Environment

Atmospheric corrosion behavior of pure Al 1050 A, 5A02 and 6A02 aluminum alloys exposed to a tropical marine environment for 4 years was investigated. Synergetic effect of Cl-deposition rate and time of wetness resulted in an abnormal increase in weight loss and a significant fluctuation in corrosion rate. Pitting corrosion occurred on the three metals. Pits on 5A02 alloy were easy to initiate and inclined to propagate laterally to form higher corrosion area and shallower corrosion pits, while pits on 6A02 alloy presented the opposite appearances. This was further confirmed by the cyclic polarization experiments.

Atmospheric corrosion of carbon steel in acid rain by accelerated weathering test

In this work, the accelerated weathering test of immersion-wet-dry combined cycles was carried ont. The artificial acid rain of NaHSO3-(NH4)2SO4-H2SO4 solution system was selected as immersion solution. Acidity of artificial acid rain affected corrossion weight loss of carbon steel, and pH 4.1 was found to be a critical point. Anodic reaction resistance of the samples during accelerated weathering test increased with exposed time by electrochemical measurement.

An Early Stopping-Based Artificial Neural Network Model for Atmospheric Corrosion Prediction of Carbon Steel

The optimization of network topologies to retain the generalization ability by deciding when to stop overtraining an artificial neural network(ANN)is an existing vital challenge in ANN prediction works.The larger the dataset the ANN is trained with,the better generalization the prediction can give.In this paper,a large dataset of atmospheric corrosion data of carbon steel compiled from several resources is used to train and test a multilayer backpropagation ANN model as well as two conventional corrosion prediction models(linear and Klinesmith models).Unlike previous related works,a grid search-based hyperparameter tuning is performed to develop multiple hyperparameter combinations(network topologies)to train multiple ANNs with mini-batch stochastic gradient descent optimization algorithm to facilitate the training of a large dataset.After that,one selection strategy for the optimal hyperparameter combination is applied by an early stopping method to guarantee the generalization ability of the optimal network model.The correlation coefficients(R)of the ANN model can explain about 80%(more than 75%)of the variance of atmospheric corrosion of carbon steel,and the root mean square errors(RMSE)of three models show that the ANN model gives a better performance than the other two models with acceptable generalization.The influence of input parameters on the output is highlighted by using the fuzzy curve analysis method.The result reveals that TOW,Cl-and SO2 are the most important atmospheric chemical variables,which have a well-known nonlinear relationship with atmospheric corrosion.

Influence of acid deposition on atmospheric corrosion of zinc

Site exposure tests both open and sheltered have been carried out in acid deposition area in Southwest China. Results from six sites show that acid deposition exerts a great influence on atmospheric corrosion of Zn, and it is more serious in wet condition. Basically, Zn corrosion is directly proportional to time of exposure. While SO2 is the main pollutant of the atmosphere environment, Zn corrosion has a linear relationship to SO2 depositing rate and a hyperbolic to rain pH value.Observations by SEM, EDAX and X-ray diffraction show that under sheltered exposure condition, the corrosion products of Zn in heavy acid deposition area principally are sulphates.Based on the corrosion rates measured, the working life of galvanized steel can be predicated.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.

Understanding environmental impacts on initial atmospheric corrosion based on corrosion monitoring sensors

Atmospheric corrosion monitoring(ACM)sensors were employed to study the initial atmospheric corrosion of carbon steels over a one-month period in six outdoor dynamic atmospheric environments in China.Based on the~250,000 corrosion data sets collected,the environmental impacts of relative humidity,temperature and rainfall on the initial corrosion behavior of carbon steels were investigated.The results showed that rainfall was the strongest environmental factor influencing the initial atmospheric corrosion rate.Relative humidity significantly influenced the corrosion of carbon steels in low-precipitation environments and non-rainfall period.

An improved deep forest model for forecast the outdoor atmospheric corrosion rate of low-alloy steels

The paper proposes a new deep structure model,called Densely Connected Cascade Forest-Weighted K Nearest Neighbors(DCCF-WKNNs),to implement the corrosion data modelling and corrosion knowledgemining.Firstly,we collect 409 outdoor atmospheric corrosion samples of low-alloy steels as experiment datasets.Then,we give the proposed methods process,including random forests-K nearest neighbors(RF-WKNNs)and DCCF-WKNNs.Finally,we use the collected datasets to verify the performance of the proposed method.The results show that compared with commonly used and advanced machine-learning algorithms such as artificial neural network(ANN),support vector regression(SVR),random forests(RF),and cascade forests(cForest),the proposed method can obtain the best prediction results.In addition,the method can predict the corrosion rates with variations of any one single environmental variable,like pH,temperature,relative humidity,SO2,rainfall or Cl-.By this way,the threshold of each variable,upon which the corrosion rate may have a large change,can be further obtained.

Corrosion Products and Formation Mechanism During Initial Stage of Atmospheric Corrosion of Carbon Steel

The formation and development of corrosion products on carbon steel surface during the initial stage of atmospheric corrosion in a laboratory simulated environment have been studied by scanning electron microscopy （SEM） and Raman spectroscopy. The results showed that two different shapes of corrosion products, that is, ring and chain, were formed in the initial stage of corrosion. MnS clusters were found in the nuclei of corrosion products at the active local corrosion sites. The ring-shaped products were composed of lepidocrocite （γ-FeOOH） and maghemite （γ-Fe2O2 ） transformed from lepidocrocite. The chain-type products were goethite （α-FeOOH）. A formation mechanism of the corrosion products is proposed.

Insight into atmospheric corrosion evolution of mild steel in a simulated coastal atmosphere

The corrosion behavior of mild steel in a simulated coastal atmosphere environment has been investigated by the indoor accelerated wet/dry cyclic corrosion acceleration test(CCT),scanning electron microscopy(SEM),Raman spectroscopy and electrochemical measurements.During the CCT test of 60 cycles,the evolution of logarithmic(corrosion rate)vs.logarithmic(CCT cycles)presents a turning point at the 5th cycle,presenting a tendency to increase first and then decrease to gradually stabilize as the CCT cycle prolonged.Before the 5th cycle,γ-FeOOH andβ-FeOOH and Fe_(3)O_(4)were detected,respectively.And then,α-FeOOH as a new chemical composition was detected in the subsequent corrosion cycles.It is found that,after long term corrosion,the rust separated into a relatively dense inner layer rich withα-FeOOH and a loose outer layer rich withγ-FeOOH,both of which have poor electrical conductivity.The rapid increase of corrosion rate in the early stage since reducible corrosion products are involved in the reduction process of the cathode which promotes the dissolution of the anodic metal substrate.Afterward,as the rust layer thickens,the resistance of the rust increases,and the aggressive ions diffusion is blocked,gradually suppressing the electrochemical corrosion process.At last,when the composition and distribution of the rust layer remain stable,the corrosion presents a fluctuating speed around a certain value during the cracking and self-repairing process of the rust layer.

Atmospheric Corrosion of Q235 Carbon Steel and Q450 Weathering Steel in Turpan,China

Q235carbon steel and Q450 weathering steel were exposed to the hot and dry environment of Turpan,China for three years.The corrosion rates of both steels were calculated and compared.The morphologies of the rust layer products were observed by optical microscopy and scanning electron microscopy.Analyses of the rust layers were performed by X-ray photoelectron spectroscopy,X-ray powder diffraction,and Raman spectroscopy,and analysis results indicate that the compositions of rust are main iron rich oxide such as FeOOH,Fe_3O_4,and Fe_2O_3.The iron oxide layer content proportion was calculated through a semi-quantitative algorithm.The resistance elements（Cr,Ni,and Cu）enhanced the resistance properties of the Q450 weathering steel matrix.Moreover,the resistance elements increased the proportion of goethite crystals in the corroded rust layer.