Corrosion Defects Research Articles

Finite element modeling of hydrogen atom diffusion and distribution at corrosion defect on aged pipelines transporting hydrogen

Repurposing existing natural gas pipelines for hydrogen transport has attracted wide interests. However, the corrosion defect present on these aged pipelines can affect hydrogen (H) atom accumulation, potentially causing hydrogen embrittlement. In this work, a finite element-based model was developed by coupling solid mechanics and H atom diffusion to investigate the distribution of H atoms at a corrosion defect on a steel pipe segment under applied longitudinal tensile strains. The applied strain causes local stress (both Mises stress and hydrostatic stress) and strain concentrations at the corrosion defect, affecting the H atom diffusion and distribution. In the absence of the tensile strain, the H atoms, once entering the interior of pipe, diffuse uniformly into the pipe body along the radial direction driven by a concentration gradient. When a strain is applied on the pipe, the H atom diffusion is driven by hydrostatic stress. The maximum H atom concentration exceeds the initial concentration of H atoms entering the steel pipe, indicating the H atom accumulation at the corrosion defect. The applied tensile strain also affects the location where the H atoms accumulate. For both internal and external corrosion defects, more H atoms will be concentrated at the defect center when the defect length reduces and the depth increases.

Stress and Corrosion Defect Identification in Weak Magnetic Leakage Signals Using Multi-Graph Splitting and Fusion Graph Convolution Networks

Weak magnetic flux leak detection is one of the most important non-destructive testing and measurement methods for pipelines. Since different defects cause different damage, it is necessary to classify the different types of defects. Traditional machine learning methods of defect type identification mainly use feature analysis methods and rely on expert a priori knowledge and the ability of designers. These methods have the following weaknesses: a priori knowledge needs to be designed iteratively, and a priori knowledge design relies on expert experience. In recent years, the rapid development of deep learning methods in the field of machine vision has led to the development of defect analysis in the industry. However, most deep learning methods lack the ability to analyze both detailed information and the overall structure. In this paper, we propose graph convolution networks for splitting and fusing multiple graphs of detail graphs and a root graph. Detail information (detail graphs) provides detailed information for the detection of WMFLs. The structure information (root graph) provides structural information for the detection of WMFLs. This paper uses simulation data and experimental data to verify that the proposed method can identify stress defects and corrosion defects well. The paper explains the experimental results in detail to demonstrate the superiority of the method in industrial methods.

Automatic detection of internal corrosion defect in a natural gas gathering pipeline using improved YOLOv5 model

The detection of internal corrosion of the very long gas pipeline is a fundamental task for the prevention of possible failures, also one of the major challenges facing gas companies. Pipeline endoscopy based on the corrosion inspection method provides direct visual observation of defects, but the post-video analysis is time-consuming and not practical. In this work, we propose an improved YOLOv5 model-based software approach to automatically detect inner corrosion defects in nature gas-gathering pipelines. Video streaming of pipe interiors is provided by an endoscope robot. Sample augmentation strategies such as affine transformation and defect segmentation with background fusion are used to generate defect images and expand the data set. The region-based recursive localization method can be effectively optimized to improve the localization of corrosion regions.

Classification of Corrosion Flaws on Front and/or Back Surfaces of Non-Magnetic Metal Plates Using a Rectangular Wave Eddy Current Testing System

If a rectangular wave excitation current is used for eddy current testing (ECT) instead of a sinusoidal wave, multifrequency testing can be performed directly because rectangular waves contain a fundamental wave as well as harmonic waves. Furthermore, considering the skin effect, it is possible to determine whether the specimen has a corrosion flaw on the front surface, back surface, or flaws on both surfaces. In this study, we first evaluate a method to classify these flaws on non-magnetic metal plates using rectangular wave ECT (RECT) systems with a linear amplifier. Here, we present an indicator in which each harmonic amplitude is divided by its fundamental amplitude. The results indicate that the amount of attenuation of the indicator in relation to the frequency depends on the type of flaw; therefore, we can classify the type of flaw using the indicator. Subsequently, we developed a RECT system with an inverter and conducted the same experiment. The results indicate that the tendency is the same as that when using the RECT system with a linear amplifier, which contributes to high efficiency, low cost, and weight reduction.

A Composite Approach of Electromagnetic Acoustic Transducer and Eddy Current for Inner and Outer Corrosion Defects Detection

In the production and service of pipelines, automated electromagnetic detection is widely employed to diagnose potential defects. However, the single inspection method can hardly multiposition detect detection simultaneously due to limited signal features. In this article, a novel composite approach of electromagnetic acoustic transducer (EMAT) and eddy current (EC) is proposed to detect different kinds of defects by combining their technical merits. A comprehensive theoretical analysis of the composite approach is given to derive the modified model of the send-receive mode. The influences of the critical parameters on hybrid signals are discussed and the probe performance is improved by over 65% in magnitude. Then, the time-division multiplexing strategy is utilized to separate hybrid signals. Finally, laboratory experiments are conducted to extract independent features and diagnose potential defects in the steel plate. Results indicated that the proposed approach could achieve a good performance in the detection task of inner and outer defects. Compared with existing detection methods, our proposed approach has significant merits in detectability and efficiency.

On the effect of coatings and pre-corrosion during fatigue tests of 7075-T6 aluminum alloy monitored with acoustic emission (AE)

Strength hardened aluminum alloys as 7075-T6 al are widely used in aeronautical industry due to their low density and high mechanical properties. Their specific microstructural composition makes them sensitive to corrosion damage at intermetallic particles. Aeronautical parts are often submitted to corrosive environments and fatigue loadings. For safety and economic matters, it is important to be able to monitor the development of damages during application. In this context, Acoustic Emission (AE) is a useful tool to monitor the state of material damage and predict its remaining useful lifetime. This work, which is part of a larger European project (Early detection and progress monitoring and prediction of corrosion in aeronautic Al alloys through calibrated Ultrasonic-CorROSion Sensor application), has for main objective to understand, identify and quantify, via AE, how corrosion defects impact the fatigue behaviour of aluminum alloy 7075-T6 specimens and covered with different types of coatings (top coat, primer and a conversion coating obtained by anodizing process). Therefore, tensile-tensile fatigue tests (R? = 0.1) monitored with AE are performed at room temperature on non-corroded samples and on corroded samples. Precorrosion defects are generated by the complete immersion of the samples in an NaCl bath (3.5% wt). Pre-corrosion defects tend to decrease the fatigue lifetime of the material tested and create damage in the substrate and coatings generating new AE sources. For all types of coated specimens, damage indicators based on the AE activity are studied in order to find characteristic damage times giving information on the remaining useful lifetime of the material during fatigue tests. Characteristic times linked to damage initiation in the substrate and propagation the main fatigue crack in the material are defined.

A Novel Assessment Method to Identify the Interaction between Adjacent Corrosion Defects and its Effect on the Burst Capacity of Pipelines

A Novel Assessment Method to Identify the Interaction between Adjacent Corrosion Defects and its Effect on the Burst Capacity of Pipelines

Research on geometric inverse problem based on the firefly conjugate gradient method

In this paper the 2-D steady-state heat transfer geometric inverse problem is solved using the finite element method, conjugate gradient method, and firefly algorithm. Based on the finite element method for solving the forward heat transfer model, and based on continuous iterative optimisation of the conjugate gradient method, the accuracy of the error function of the measured and estimated values is kept within a certain range, so that the geometry of the object under test can be calculated in an inverse way. In the study of the forward problem, the temperature field distribution is solved using circular pipes as the research objects, and the feasibility of applying the finite element method to heat transfer problems is verified. The inverse problem takes the circular tube as the object and considers two different corrosion defects on the inner wall of the circular tube. Simultaneously, the firefly algorithm is introduced based on the conjugate gradient method to stochastically optimize the temperature data and suppress the fluctuation of the inversion result. Numerical experiment results indicate that the method in this paper can perform more accurate geometric shape recognition when there is a certain temperature measurement error or the temperature measurement information is relatively complete.

Integrity assessment of supercritical CO2 transport pipelines

With global warming, carbon capture and storage (CCS) technology is attracting increasing interest as a major technology for carbon peaking and carbon neutrality. Pipeline transportation, as one of the most cost-effective modes of transportation, has become the major transport method for large-scale long-distance supercritical carbon dioxide (CO2) transportation. Because corrosion is a major factor affecting pipeline operation, this paper aims to assess the integrity of supercritical CO2 pipelines. A finite element model of the pipeline with corrosion defects is created based on the corrosion morphology of the supercritical CO2 pipeline, and sensitivity analysis of the parameters affecting the burst pressure of the supercritical CO2 pipeline is carried out. Based on finite element analysis and burst pressure model of the intact pipeline, a nonlinear fitting method is used to establish the burst pressure equation of supercritical CO2 pipelines with corrosion defects. Compared to experimental data, the predictive equation has a high accuracy for the burst pressure of X60-X80 steel pipelines. It can serve as a reference for the design and integrity assessment of supercritical CO2 pipelines.

Experimental study of the effects of semi-elliptical defects on the API X52 pipeline and its reparation by welding

The aim of the project is to study experimentally the influence of the semi-elliptical defect on the steel of grade API 5L X52 pipeline and its reparation by welding operation to keep the safety of hydrocarbons transport network. The tests have been performed on the specimens with/without semi-elliptical defects by using two ratios a/c and a/t, where the defects issue on the piping systems wall is treated by using the welding operation, which focuses on the filling the defected surface as same thickness of the base wall of the pipeline after removing the defects. The decrease of ultimate stress is mainly evident depending on the size of crack, where they compared to the base metal results. The experimental results showed that the reliability of the welding operation is proved especially in the ratio a/c =1, which is similar to that found in automatically welded. It is proved that the ratio a/t = 0.2 curve exhibits similarity to the base metal curve and their elongation conforms to API standard of steel X52 grade. Clearly, corrosion defects cause degradation of mechanical property in the order of 44% to 50% depending on the ratio of 0 < a/c ≤1 and from 20% to 80% according to the second ration of 0 < a/t ≤0.8. The obtained results proved that the enhanced of mechanical properties by welding reaches to ultimate stress is 559 MPa for the ratio a/t = 0.2 and 531 MPa for the ratio a/t = 0.5. Finally, the experimental results provided that the impact of semi-elliptical defect has effects on the safety of piping systems where welding became as one of among solutions to repair the piping systems.

A comparison between computer vision- and deep learning-based models for automated concrete crack detection

Systems subjected to continuous operation are exposed to different failure mechanisms such as fatigue, corrosion, and temperature-related defects, which makes inspection and monitoring their health paramount to prevent a system suffering from severe damage. However, visual inspection strongly depends on a human being’s experience, and so its accuracy is influenced by the physical and cognitive state of the inspector. Particularly, civil infrastructures need to be periodically inspected. This is costly, time-consuming, labor-intensive, hazardous, and biased. Advances in Computer Vision (CV) techniques provide the means to develop automated, accurate, non-contact, and non-destructive inspection methods. Hence, this paper compares two different approaches to detecting cracks in images automatically. The first is based on a traditional CV technique, using texture analysis and machine learning methods (TA + ML-based), and the second is based on deep learning (DL), using Convolutional Neural Networks (CNN) models. We analyze both approaches, comparing several ML models and CNN architectures in a real crack database considering six distinct dataset sizes. The results showed that for small-sized datasets, for example, up to 100 images, the DL-based approach achieved a balanced accuracy (BA) of ∼74%, while the TA + ML-based approach obtained a BA > 95%. For larger datasets, the performances of both approaches present comparable results. For images classified as having crack(s), we also evaluate three metrics to measure the severity of a crack based on a segmented version of the original image, as an additional metric to trigger the appropriate maintenance response.

Maintenance strategy optimization of pipeline system with multi-stage corrosion defects based on heuristically genetic algorithm

To ensure the high reliability of the pipeline system, it is necessary to take group maintenance actions. This work proposes an optimal group maintenance approach based on a heuristically genetic algorithm to attain the system-performing goal while minimizing overall costs with assured system reliability. Multi-stage corrosion defects and multi-level risk areas are considered in this novel approach. The proposed method can sufficiently avoid pipeline failures by considering the multi-level probability of failure constraints. The methodology is illustrated by taking the 60-segment pipelines with multiple corrosion defects as an example. Numerical studies show that the proposed methodology can find an optimized maintenance strategy with a lower cost compared with the unified batch maintenance strategy. In addition, an optimal dynamic maintenance model is proposed and compared with the static model when the environment of the pipelines varies. Sensitivity analyses of the physical parameters of the phenomenon and the tuning parameters of the data-driven model show that the method has good effectiveness, compatibility, and universality.

용접부 샌드 블라스팅 표면처리에 따른 부식 영향 연구

Recently, consumer complaints on car corrosion have been steadily increasing. The main cause of corrosion is calcium chloride, which is commonly used in winter, and the lower parts of the car, such as suspension, are more affected by it. Corrosion affects the parts durability by weakening them and threatening the passenger safety if exposed to continuous loads. Therefore, herein, a method of improving corrosion performance was studied by applying the surface treatment to the welding part of the steel plate used in the manufacture of cross members among automobile suspension parts. Specimens were manufactured through brushing and the sand blasting surface treatment, and cross-cut adhesion tests and repeated corrosion tests were conducted. The test results showed that the cause of the electrodeposition coating and corrosion defects was the oxide layer formed from oxidation after welding, and the sand blasting surface treatment was very effective in removing the oxide layer.

Effect of Protection on Guy Wire Related to Corrosion Defects

Guy wires are a powerful mechanical tool used widely in all industries. Most of the applications are employed in supporting tall structures such as antenna, communication towers, transmission lines, electric poles, and erecting flare stacks on an oil and gas platform or plant. Severe wind events such as tornadoes are the primary failurein transmitting line structure in many places worldwide. So, this research aims to investigate the effect of different types of guy wire on corrosion defects. There are many lay and strand design types in the production of guy wire. The two most common are the 7-wires and 19-wires lay. There are four samples with four conditions: the first sample is not protected with any material, the second is protected by lubrication using WD-40, the third is protected using rubber hose casing, and the last is protected by a combination of both lubrication and rubber hose casing technique. The result shows that the sample protected by a combination of lubrication and rubber hose casing has no corrosion defect.

Dynamic response and safety assessment of inner‐wall corroded concrete pipeline in service subjected to blasting vibration

AbstractBuried pipelines in urban area are prone to corrosion defects for many years. Ensure the safety of buried corrosion pipelines is a key concern during tunnel blasting excavation. Based on the blasting engineering along Shenzhen Metro Line 12, the field test of full‐scale concrete pipeline adjacent blasting was implemented. The dynamic response of concrete pipeline induced by blasting vibration was analyzed by using the dynamic finite element numerical simulation method, and the reliability of numerical simulation was verified by the field monitoring data. On this basis, considering the corrosion defect morphology of pipeline, the distribution characteristics of peak particle velocity and peak effective stress of concrete pipeline with different corrosion depths, corrosion widths, and corrosion lengths induced by blasting vibration were discussed. The parameter analysis method was used to research the influence of corrosion morphology parameters on the dynamic response of the pipeline, and the corrosion depth of the inner‐wall of the pipeline was defined as the main control parameter of the dynamic response. According to the failure criteria of concrete materials, the safety criterion of corroded concrete pipelines with different service years subjected to blasting vibration was established.

Ultrasonic guided wave testing on pipeline corrosion detection using torsional T(0,1) guided waves

Ultrasonic guided wave testing (UGWT) is used in rapid screening to detect, locate and classify corrosion defects. This non-destructive testing technique can perform wide-range inspection from a single point, thus reducing the time and effort required for NDT. However, the mode conversion phenomena and the dispersive nature of the guided waves make corrosion detection difficult. Hence, the parametric studies on the response signals of a T (0, 1) wave from pipe defects were presented in this paper. Firstly, a mathematical model of 6-inch schedule 40 pipes was developed. The corrosion profile of various geometries was then constructed on the outer surface of the pipeline by varying the circumferential length and depth. The numerical study was performed to analyse the characteristics of the response signals when a torsional guided wave impinges on the corroded pipelines. A five-cycle Hanning tone-burst signal with a central frequency of 30k Hz was used throughout the study. The results demonstrated that mode conversion to a flexural mode F (1, m) occurs when the stimulated T (0, 1) strikes non-symmetric defects. Nonetheless, as the circumferential extent of the corrosion increased, the response signals tended to behave symmetrically, and there was less mode conversion detected. Thus, the presence of flexural mode F (1, m) can be used as the criteria to distinguish symmetric and asymmetric faults. In addition, the results demonstrated that the reflection coefficients increase monotonically with the defect's depth due to the increases in the estimated cross-sectional area loss (ECL). As a result, a more significant proportion of the transmission wave was reflected. These findings serve as guidelines for on-site inspections. With the known speed of guided wave propagation, it is possible to precisely forecast the position of faults.

Effects of corrosion defect growth on submarine pipeline under operating pressure and axial displacement

Corrosion defect growth with time seriously threatens the safe operation of submarine pipelines and the study about its effects on strength degradation is essential for pipeline integrity assessment. In this work, a three-dimensional finite element model was developed to simulate the defect growth on pipeline exposed to sea mud environment based on multiphysical field coupling and deformed geometry. The deeper defect and larger operating pressure (OP) enhance local stress concentration and corrosion rate. The corrosion rate decreases first and then increases with the axial displacement (AD) of pipeline. The OP causes pipelines to corrode preferentially on the defect bottom while AD trends to form uniform corrosion on the total defect surface. There is an anti-synergistic effect between OP and AD on pipe thinning. A residual service life estimation method based on the unsteady multi physical field simulation was proposed for the submarine pipeline.

DR detection process analysis for weld of pressure-bearing special equipment

Due to the complex and harsh operating environment of pressure-bearing special equipment, the occurrence of accidents is very harmful, so its safety performance is very important. At present, the smelting and machining technology of related raw materials and components is very mature, but the toughness of the weld metal generally lags behind that of the base metal, which has become the weakest link in pressure-bearing special equipment. Especially in long-term operation under complex working conditions such as high temperature, high pressure, and vibration, it is easy to produce fatigue, corrosion defects, or cause the expansion of residual defects in manufacturing and installation. This paper will analyze and introduce the digital ray (DR) detection process of weld of pressure-bearing special equipment, and provide a certain reference for the correct use of digital ray technology.

Quality evaluation of organic protective paints using terahertz pulse imaging technology based on wavelet packet energy method

It is particularly important to make quality evaluation for paint spraying process. This work presented an efficient method based on wavelet packet energy for terahertz non-destructive evaluation of organic protective paint. The wavelet packet energy analysis algorithm was summarized. Various coating structures were experimentally investigated using terahertz pulsed imaging system and the relative wavelet energy and the Shannon entropy of the detected signal were calculated as wavelet energy indexes. The proposed algorithm was performed on the evaluation of coating unevenness and the identification of hidden corrosion defect. The results demonstrated that the wavelet energy indexes are sensitive to coating structure change when compared to the terahertz peak-finding method, and it allowed more accurate estimate of micro corrosion defect. Therefore, the proposed approach based on wavelet packet energy could be recommended for quick quality evaluation of organic coating with terahertz non-destructive technology.

Cause analysis on abnormal failure of copper-substrate pin fin heat sink for new energy vehicle

The new energy vehicles are playing more and more important role in energy conservation and environmental protection. With regard to the new energy vehicles, the power module is a key device which converts the direct current (DC) into the alternating current (AC). Considering a great deal of heat generated by the power module during operating, a kind of pin fin heat sinks with nickel-phosphorus coating is specially designed and manufactured, so as to prevent the power module from thermal damage. In view of this, the reliability of the pin fin heat sinks must be strictly evaluated before putting into use. However, during the corrosion resistance tests, some suspected corrosion defects occurred on the pin fin heat sinks, by which the newly-designed pin fin heat sinks were judged as unqualified. Aimed at this special failure, a series of characterization methods and comprehensive analysis were carefully performed. Through systematic assessment and analysis, the so-called local corrosion was excluded and the explosive release of local hydrogen in nickel-phosphorous coating was determined as the root cause of radial defects. Meanwhile, four kinds of typical manufacturing defects for the pin fin heat sinks were characterized and discussions were also given in detail for the formation causes and affecting factors. Based on the obtained conclusions, the effective countermeasures are put forward for improving plating quality and the achievement of the paper is also helpful for better understanding the operating safety and reliability of new energy vehicles.