Corroded Steel Plates Research Articles

Nonlinear Wave Modulation for the Evaluation of Corroded Steel Plates Embedded in Concrete

Nonlinear Wave Modulation for the Evaluation of Corroded Steel Plates Embedded in Concrete

Prediction model of fatigue crack propagation life of corroded steel plate considering pit characteristics

Pitting corrosion notably increases stress concentration, thus accelerating fatigue crack initiation and propagation at the pit base. This research quantifies the relationship between pit dimensions and fatigue crack development by introducing crack extension ratios (γa​ and γc)​. Employing a series of finite element models, the influence of pit characteristics on the stress intensity factor (K) at the crack tip is assessed. Based on these assessments, a formula for computing the K-value is proposed. Furthermore, a two-stage fatigue life prediction model for both partial and complete penetration is developed using the Paris equation. Results indicate that pits substantially affect the K-value during partial penetration. Specifically, as γa approaches zero, the K-value approaches zero, and as γa approaches one, it aligns with the K-value of a semi-elliptical surface crack. Conversely, in the complete penetration phase, the influence of the pit on the K-value is negligible, and the K-value can be calculated according to the plate with a central penetrating crack. Experimental validation confirms that the model generally maintains a prediction error within 10%.

Load Capacity Prediction of Corroded Steel Plates Reinforced with Adhesive and High-Strength Bolts Using a Particle Swarm Optimization Machine Learning Model

A machine learning (ML) model, optimized by the Particle Swarm Optimization (PSO) algorithm, was developed in this study to predict the shear slip load of adhesive/bolt-reinforced corroded steel plates. An extensive database comprising 490 experimental or numerical specimens was initially employed to train the ML models. Eight ML algorithms (RF, AdaBoost, XGBoost, GBT, SVR, kNN, LightGBM, and CatBoost) were utilized for shear slip load prediction, with their hyperparameters set to default values. Subsequently, the PSO algorithm was employed to optimize the hyperparameters of the above ML algorithms. Finally, performance metrics, error analysis, and score analysis were employed to evaluate the prediction capabilities of the optimized ML models, identifying PSO-GBT as the optimal predictive model. A user-friendly graphical user interface (GUI) was also developed to facilitate engineers using the PSO-GBT model developed in this study to predict the shear slip load of adhesive/bolt-reinforced corroded steel plates.

Mechanical Properties and Cooperation Mechanism of Corroded Steel Plates Retrofitted by Laser Cladding Additive Manufacturing under Tension.

As a metal additive manufacturing process, laser cladding (LC) is employed as a novel and beneficial repair technology for damaged steel structures. This study employed LC technology with 316 L stainless steel powder to repair locally corroded steel plates. The influences of interface slope and scanning pattern on the mechanical properties of repaired specimens were investigated through tensile tests and finite element analysis. By comparing the tensile properties of the repaired specimens with those of the intact and corroded specimens, the effectiveness of LC repair technology was assessed. An analysis of strain variations in the LC sheet and substrate during the load was carried out to obtain the cooperation mechanism between the LC sheet and substrate. The experimental results showed that the decrease in interface slope slightly improved the mechanical properties of repaired specimens. The repaired specimens have similar yield strength and ultimate strength to the intact specimens and better ductility as compared to the corroded specimen. The stress-strain curve of repaired specimens can be divided into four stages: elastic stage, substrate yield-LC sheet elastic stage, substrate hardening-LC sheet elastic stage, and plastic stage. These findings suggest that the LC technology with 316 L stainless steel powder is effective in repairing damaged steel plates in civil engineering structures and that an interface slope of 1:2.5 with the transverse scanning pattern is suitable for the repair process.

Experimental study on bond behavior between wet lay-up CFRP and corroded steel plates

Corrosion of steel in marine environments is a major safety concern for marine steel structures throughout their service lives. Strengthening these corrosion-damaged structures with carbon fiber-reinforced polymer (CFRP) shows great potential for extending their service lives. However, the bond behavior between CFRP and corroded steel, especially the influence from adhesive properties and corrosion degree, has not been fully understood. This paper therefore presents the results of a comprehensive experimental study on the bond behavior between wet lay-up CFRP and corroded Q355B steel plates. Tensile tests on double-lap CFRP-to-steel joint specimens with different bonded lengths, adhesives and corrosion durations were then conducted. The failure modes, load-displacement curves, strain and local shear stress distributions, effective bond lengths, and bond-slip relationships of the test joint specimens were investigated in detail. The result showed that the influence of corrosion on the CFRP-to-steel bond performance varied depending on the failure modes resulting from the material properties of adhesives. However, corrosion has insignificant influence on the general patterns of load-displacement curves, strain distribution, local shear stress distribution, local bond-slip curves with same adhesives. When failure occurred in the adhesive or the steel-adhesive interface, the corrosion tended to have a more accentuated effect on the bond performance.

Stress concentration factor estimation for corroded steel plates using the surface gradient method

Pitting corrosion occurs in steel components as a stress-accumulating surface irregularity that is vulnerable to fatigue crack nucleation. In this study, stress distribution in sinusoidal surfaces was investigated to devise an estimation method for the stress concentration factor (SCF) fluctuations of corroded steel. An SCF equation for sinusoidal surfaces was developed from empirical data based on three parameters: wavelength, thickness, and position. For corroded surfaces, successive numerical differentiations can be performed on each point to determine the sinusoidal surface having a point sharing the same gradient information. Notably, the SCFs of corresponding points are comparable; SCF estimation is made feasible for irregular surfaces through sinusoidal surfaces. In two-dimensional sections, maximum error was below 5% at pits and 15% for the surface. In three-dimensional models, maximum error was below 20% at pits for wide-ranging corroded specimens. Therefore, the proposed method effectively estimates SCF for identifying areas at risk of fatigue cracking.

Corrosion damage identification based on the symmetry of propagating wavefield measured by a circular array of piezoelectric transducers: Theoretical, experimental and numerical studies

The article investigates the results obtained from numerical simulations and experimental tests concerning the propagation of guided waves in corroded steel plates. Developing innovative methodologies for assessing corrosion-induced degradation is crucial for accurately diagnosing offshore and ship structures exposed to harsh environmental conditions. The main aim of the research is to analyze how surface irregularities affect wave propagation characteristics. An investigation was conducted for antisymmetric fundamental mode A0. Specifically, the study examines the asymmetrical wavefronts generated by nonuniform thickness in damaged specimens. Initially, numerical analysis explores the impact of thickness variation on wave field symmetry. Corroded plates with varying levels of degradation are modeled using the random fields approach, with degradation levels ranging from 0 % to 60 %. Subsequently, the research investigates how the standard deviation of thickness distribution (from 5 % to 20 % of the initial thickness) and excitation frequency (from 50 to 150 kHz) influence recorded signals and the shape of reconstructed wavefronts. Each scenario compares wavefront symmetry levels estimated using rotational and bilateral symmetry degrees as indicative parameters. The numerical simulations are complemented by experimental tests conducted on plates with three different degradation levels. The results demonstrate the efficacy of the proposed wave field analysis approach for assessing structural integrity, as evidenced by the agreement between numerical predictions and experimental observations.

Performance assessment of corroded stiffened steel plates considering non-Gaussian spatial correlated corrosion random field

This paper investigates the effect of corrosion randomness on the compression performance of stiffened steel plates. An anisotropic non-Gaussian random filed model is proposed to characterize the corrosion depth of the corroded steel plate surface. The specimens of corroded steel plate were obtained utilizing the artificial climate environment method. Corrosion characteristics were measured through 3D-scanning and reverse modeling. Statistical methods are utilized to analyze corrosion depth, including probability distribution and correlation coefficient. Two models are proposed for steel plate placing flatly and inclinedly, respectively. It is found that for both models corrosion depth follows truncated GEV distribution, and the correlation coefficient follows a bidirectional exponential function. To investigate the effect of non-Gaussian and correlation characteristics on bearing capacity, the proposed model is used for generating anisotropic non-Gaussian corrosion random fields for stiffened steel plates. Generated samples were used for finite element analysis. It is found the ignorance of non-Gaussian or correlation of the corrosion depth field will underestimate the deterioration of bearing capacity of stiffened steel plates. Finally, a parametric study on the correlation coefficients of the corrosion field indicates that correlation length will affect the residual bearing capacity of corroded steel plate. The proposed random field for corrosion depth of steel plate could be used for potential application on the safety assessment of corroded steel structures.

An analytical approach to predict fatigue strength of corroded steel plates using random field-based corrosion surface modeling

This study introduces a probabilistic method to predict the fatigue strength of corroded steel members by incorporating uncertainties related to corrosion depth and surface morphology using random field modeling. The modeling successfully captured the probability density of the target corrosion depth, accurately representing corrosion geometric characteristics. Validation against fatigue testing on corroded rolled beams showcased the method’s accuracy across a range of stress levels. The application of the proposed method for time-variant fatigue strength predictions unveiled a rapid decline in both fatigue constant A and the constant amplitude fatigue threshold (CAFT) during the initial stages of corrosion. In marine and urban environments, fatigue strength fell rapidly within the first 3 years after corrosion initiation, whereas in rural environments, fatigue strength was anticipated to start to decline gradually after 5 years. These projections underscore the necessity of regular inspections to assess the condition of protective coatings. Moreover, the degradation curves generated by this method can serve as a foundational element in establishing an effective maintenance strategy for structures.

Quantitative method for evaluating corrosion defects and residual bearing capacity of bridge structural steel via MMM technique

The quantitative assessment of corrosion defects and residual bearing capacity is essential to ensure the safe operation of bridge steel structures. In this study, Q345qD steel was selected as the research object, and specimens with different corrosion levels were prepared using the electrochemical corrosion method. Metal magnetic memory (MMM) detection experiments and uniaxial tensile experiments on corroded steel plates were performed. A three-dimensional magnetic charge model of a corroded steel plate considering the end effect was built to explain the variation of the MMM signals. The finite element simulation results of the corroded steel plates were consistent with the experimental and theoretical results. Based on experimental and finite element data, the quantitative relationship between the corrosion depth h and the magnetic characteristic parameter Hn(z) is established with a relative error within 15 %. A quantitative relationship between the nominal tensile strength σu and the magnetic characteristic parameter Hn(z) is proposed with an evaluation accuracy within ±5 MPa. It is suggested that the proposed evaluation method is feasible in quantitatively evaluating the defects and residual tensile strength of corroded steel plates using the MMM technique.

Shear capacity of corrugated steel plates with a random corrosion damage

Corrugated steel plates have been utilized widely in engineering structures, such as underground utility tunnels, web of steel beams, underground pipelines, and shear walls. The influence of corrosion on the buckling capacity of corrugated steel plates differs from that of flat steel plates. A numerical model of corrugated steel plates with random corrosion is initially established and validated using theoretical results. The influence of pitting corrosion on the shear capacity of corrugated steel plates is investigated through stochastic numerical analysis. The influences of geometric parameters, including pitting size, plate thickness, and corroded thickness, on the shear capacity of randomly corroded steel plates are also investigated. In addition, the changing trend of shear capacity along with mass loss ratio is derived.

Compression capacity of corroded plates with three sides simply supported and one side free

Steel plates have been widely used in various structures, including building structures, bridges, ocean platforms, and industrial equipment. The ultimate strength of steel plates can be substantially affected by corrosion. The influence of corrosion on ultimate strength of steel plates with three sides simply supported and one side free is quantified. The stochastic numerical analysis is adopted and the reliability of established stochastic FE model is firstly verified by comparing with analytical results. The feasibility of derived results for steel plates with different width- thickness ratios (b/t) ratios is investigated. The analytical formulas for predicting the reduction factor Θ are proposed. The influence of aspect ratio, geometrical imperfection and corroded thickness on the changing rule of reduction factor along with mass loss ratio are systematically investigated. The conclusion can establish a foundation for the buckling behavior of corroded steel plates.

Application of neural networks to the prediction of the compressive capacity of corroded steel plates

The application of artificial neural network approaches has been successful in solving complex civil engineering problems, such as damage detection and structural member capacity prediction. Within the context of the present study, corrosion has become the main factor limiting the safety and load-carrying capacity of aging steel bridge girders. Corrosion damage is often most severe near girder ends in simple-span bridges due to deck joint leakage and the pooling of water and de-icing salts. In addition to empirical methods, Finite Element (FE) analysis is typically used to evaluate the residual bearing capacity of corroded steel girders. However, it is prohibitively challenging and time-consuming to create an accurate FE model of a corroded girder due to the irregular nature of corrosion damage. Resultantly, corrosion damage is often reduced to uniform section loss, which leads to unreliable estimates of a girder’s residual bearing capacity. Researchers have proposed methodologies for modeling irregular corrosion damage, but these approaches require a high level of expertise. A comprehensive method is therefore required to efficiently estimate the residual bearing capacity of a corroded steel girder. This paper proposes the use of neural networks to predict the residual bearing capacity of corroded steel plate models as a first step in estimating the residual bearing capacity of an in-service girder. Neural networks are constructed and trained on a database built from FE analysis performed on steel plate models with realistic representations of corrosion damage. This study assesses the ability of neural networks to estimate the compressive capacity of corroded steel plates since plate girders are one of the most prevalent girder forms in steel bridges. Three types of neural networks are trained to predict the compressive capacity of corroded plate models, including a multilayer perceptron (MLP), a convolutional neural network (CNN), and a hybrid MLP-CNN model. The average mean absolute percentage errors (MAPE) for the three models are 20.65%, 11.46%, and 9.64%, respectively. The results of this study demonstrate the potential of using neural networks to predict the compressive capacity of corroded plates efficiently and accurately, which could facilitate proactive maintenance decision-making for aging bridges.

Post-buckling strength of simply supported corroded square plates subjected to in-plane compression

Steel plates have been widely used in various structures, including building structures, bridges, ocean platforms, and industrial equipment. The post-buckling strength of steel plates can be substantially affected by corrosion. This study quantifies the influence of corrosion on post-buckling strength of simply supported corroded steel plates. To do so, stochastic numerical analysis is adopted, and the reliability of an established stochastic finite element model is initially verified by comparing it with the analytical results. This study also investigates the feasibility of the derived results for steel plates with different width/thickness (b/t) ratios. A variable Θ is introduced to represent the reduction factor of compression strength of corroded plates. The analytical formulas for predicting the upper and lower bounds of Θ are proposed, and the probabilistic distribution model of Θ is suggested. The method to determine the equivalent width/thickness (b/teqv) ratio of corroded steel plates is proposed. With the premise that the post-buckling strength remains unaffected, the corroded steel plates can be treated as uncorroded when the b/teqv ratio is substituted for the original b/t ratio. Conclusion of this study can establish a foundation for the buckling behavior of corroded steel plates.

Local corrosion morphology analysis and simplification of low carbon steel plates

This paper focuses on the surface morphology of low carbon steel plates with local corrosion. Copper-accelerated acetic acid salt spray tests were carried out on 24 steel plate specimens with different corrosion parameters, and then the 3D morphology of the steel plate surfaces after corrosion was observed, extracted and analyzed. According to the statistical analysis of the surface depth of the corrosion morphology, the local corrosion surface can be divided into the central flat corroded zone and edge corroded zone, and the width of the edge corroded zone almost keeps constant regardless of the corrosion area. The 3D morphology of the corroded specimens was imported into ABAQUS software to develop finite element models, and the numerical results were compared with the tensile test results of the corroded steel plates, showing good agreement. Finally, based on the finite element analysis, it is suggested that local corrosion of steel plates can be simplified into a region with uniform depth, whose depth is determined as the average corrosion depth of the locally corroded region. The maximum errors of prediction results of yield strength, ultimate strength and ultimate strain between the simplified model and the actual morphology model were 0.03%, 1.8% and 20%, respectively.

Interfacial Bond-Slip Model for CFRP Plate Externally Bonded to Corroded Steel Plate

The purpose of this study is to establish the interfacial bond-slip model for CFRP plate externally bonded to corroded steel plate. The present bond-slip models for CFRP materials bonded to uncorroded steel plate were first reviewed. Thirty-four double-lap joints were tested to investigate the effect of corrosion duration and adhesive thickness on the bond behavior between CFRP plates and corroded steel plates, and the bond-slip curves for the bonding interface with different adhesive thickness and corrosion duration were obtained combined with the CFRP plate strain distribution data. A new bond-slip model for CFRP plate externally bonded to corroded steel plate was proposed, and the expression of the characteristic parameters, which included the maximum bond resistance τf, the relative slip at the peak bond stress s1, the fitting parameter α, and the interfacial fracture energy Gf, were also developed based on the careful regression analysis of the present data. The influence of the corrosion duration and construction adhesive thickness on the bond-slip relationship were accounted together and expressed as a new parameter; that is, the effective adhesive thickness teff. The comparison between the predicted values and experimental results indicated that the proposed bond-slip model can be applied to reproduce the structural response of the CFRP plate-corroded steel plate double-lap joint with reasonable accuracy. The outcome of this study can provide meaningful references and essential data for the reliable application of CFRP strengthening systems in the performance improvement of corroded steel structures.

Three-Dimensional Morphology and Watershed-Algorithm-Based Method for Pitting Corrosion Evaluation

Pitting corrosion and stress concentration at rust pits are the principal reasons for severe degradation in fatigue performance of corroded steel structures. The accurate evaluation of rust pits on rough and uneven corrosion surfaces is the foundation of fatigue life estimation for corroded steel structures. In this paper, a new method for the identification, extraction, and evaluation of rust pits on the surface of corroded steel structures was proposed based on a three-dimensional morphology and watershed algorithm. An accelerated corrosion experiment was first executed to acquire corroded steel plates, and then surface profile measurements were conducted to obtain the three-dimensional morphology of the corroded steel surfaces. Furthermore, the surface topography data of the corroded steel surfaces were written into a gray matrix through coordinate transformation. Then, the gray matrix was successively filtered and gradient-mapped, and the watershed was calculated to obtain the pit mark matrix and pit depth matrix. A calculation method for the size and shape of rust pits was consequently developed, and a statistical analysis of the extraction results of the rust pits was also conducted. The results showed that rust pit density had a peak value at the corrosion duration of 3 months, and rust pit density showed a fluctuating process with corrosion duration that continued to increase until 15 months. The values of the depth diameter ratios of rust pits were concentrated in the range of 0.1~0.8. With corrosion duration increasing from 3 months to 4, 6, 8, 12, and 15 months, the distribution range of the depth diameter ratios of rust pits decreased at first and then increased, followed by decrease and, finally, increase. The width distribution of the rust pits was independent of the depth distribution of the rust pits. The values of the volume ratios were mostly distributed between π/12 and π/4, and the shapes of most rust pits were similar to half (ellipsoidal) spheres.

Fatigue Crack Propagation Prediction of Corroded Steel Plate Strengthened with Carbon Fiber Reinforced Polymer (CFRP) Plates.

The purpose of this study is to investigate the mechanism of improving fatigue performance and the estimation model of fatigue life for corroded steel plate strengthened with CFRP plates. A new two-stage fatigue crack propagation prediction model for the corroded steel plate strengthened with CFRP plates was proposed; moreover, the identification of critical rust pits and the equivalent method of initial cracks, and the calculation method of stress intensity factor (SIF) values at the crack tip were established. The accuracy of the proposed model was verified by comparing the predicted and tested fatigue life of the corroded steel plate strengthened with CFRP plates. Finally, the proposed two-stage crack propagation model was applied to carry out a parameter analysis to investigate the effect of weight loss rate, equivalent initial crack size, adhesive thickness, CFRP stiffness and CFRP prestress level on the fatigue crack propagation of the corroded steel plate strengthened with CFRP plates. Results showed that the maximum depth and the average width of the rust pits were suggested to be taken as the equivalent dimensions of the initial semi-elliptical surface crack for the fatigue crack propagation prediction of corroded steel plate strengthened with CFRP plates. Increasing the weight loss rate of the corroded steel plate, the initial crack size or the adhesive thickness would accelerate the crack growth and reduce the fatigue life, whereas increasing the stiffness or prestress level of the CFRP plate would significantly reduce the crack growth rate and increase the fatigue life. The smaller the initial crack size, the more sensitive the crack propagation life was to the variation of equivalent initial crack size. The influence of adhesive thickness on the fatigue life was limited and convergent, and the application of prestressing could significantly improve the utilization rate of CFRP materials and the fatigue strengthening effect of the corroded steel plate.

Nonlinear ultrasonic characteristics of a corroded steel plate

ABSTRACT Corrosion in leak-tight plate structures, such as the containment liner in Nuclear Power Plants (NPPs), is detrimental to their operational state. To tackle this issue, the present work aims to assess the feasibility of using nonlinear ultrasound to detect corrosion. The corrosion product of main concern in the present study contains several microscopic and macroscopic cracks and delaminations. Three parameters based on nonlinear acoustics were studied by using two types of measurements on a uniformly corroded steel plate. The relative parameter of quadratic nonlinearity (), given by the ratio between the second harmonic amplitude and the fundamental amplitude squared, was measured using indexed measurements with a pitch-catch setup while the specimen was immersed in water. The sideband peak count (SPC), which is a measure of the number of sidebands generated from a wide band excitation, was extracted from through-transmission measurements. The third parameter studied is a measure of the energy distributed in the sidebands over the energy at the excitation frequencies (). This parameter is determined for the same datasets used for SPC. All three parameters increased in the severely corroded region of the inspected steel plate, indicating the potential use of nonlinear ultrasonics to detect corrosion.

Stress Concentration Analysis of the Corroded Steel Plate Strengthened with Carbon Fiber Reinforced Polymer (CFRP) Plates

The purpose of this study is to investigate the stress concentration of a corroded steel plate strengthened with carbon fiber reinforced polymer (CFRP) plates. An accelerated corrosion experiment was first executed to acquire corroded steel plates, and then surface profile measurements were conducted to obtain 3D coordinate data of the corroded steel surface. Finite element models considering the surface morphology of the corroded steel plate and the interfacial bonding properties between the CFRP plate and the corroded steel plate were established to investigate the stress concentration of the corroded steel plate strengthened with and without CFRP plates. The reliability of the numerical modeling method was verified based on a mesh convergence analysis and a comparison of the fatigue test, 3D morphology scanning, and numerical analysis results. Specimens with five levels of corrosion damage, six kinds of CFRP-strengthening stiffness, five kinds of adhesive thickness, and five levels of CFRP prestress were numerically modeled. The primary indications consist of features of stress distribution, and the stress concentration factors Kt and Ktg were analyzed. Results showed that the features of stress distribution and the stress concentration factor Kt of the corroded steel plate strengthened with and without CFRP plates are only related to the shape, size, and position of rust pits, but not to the degree of uniform corrosion or the reinforcement parameters. The value of Kt for the corroded steel plate with a corrosion duration of 6~18 months and a weight loss rate of 9.16~21.78% was approximately 1.199~1.345. The converted stress concentration factor Ktg has more practical significance than the stress concentration factor Kt in describing the influence of corrosion and CFRP reinforcement on the peak tensile stress of the corroded steel plate. The value of Ktg increased linearly with the increase of the weight loss rate of the corroded steel plate and decreased appreciably with the increase of the strengthening stiffness and prestress level of the CFRP plates, and it presented a very small increasing trend with the increase of the adhesive thickness.