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Pipelines are crucial for transporting energy sources, yet corrosion especially stress corrosion cracking (SCC) poses a complex and potentially catastrophic form of material degradation. Traditional techniques like finite element analysis (FEA) have been utilized for SCC prediction, but it suffers from high computational cost and limited scalability. Deep learning (DL) with integration of FEA leverages large-scale data and learn complex nonlinear patterns for SCC prediction. Currently, literature on deep learning-enabled finite element analysis for pipelines SCC prediction is scarce, offering limited insights into this emerging approach and lack of comprehensive review. This paper reviews and investigates the current research directions and applications of DL-enabled FEA methodologies for simulation of SCC prediction. The importance of DL, technique type and network are also outlined in this review paper. This paper delves into integration of DL algorithms with FEA and their ability to grab complex interactions between mechanical stress, material properties, and environmental factors. Based on this comprehensive review, it was found that DL and FEA have proven to be strong prediction tools with high accuracy and lower training cost. DL-enabled FEA techniques are also being utilized to replace time-consuming methods and conventional codes. Furthermore, article discusses potential of this integrated approach for enhancing accuracy and efficiency of SCC prediction, leading to improved pipeline integrity management practices. [ABSTRACT FROM AUTHOR]

ABSTRACT As a common method for liquid drainage in wave‐shaped pipelines, foam drainage has been used in gas‐gathering pipelines in various oil and gas fields. One of the common problems encountered in wave‐shaped foam drainage pipelines is the inaccurate prediction of the liquid retention rate. This issue makes it difficult to predict liquid accumulation points, which affects gas output efficiency, causes pipeline corrosion, and generates natural gas hydrates. To clarify the liquid‐holding rate law of wavy foam drainage pipelines is studied. In this study, through experiments to verify the accuracy of the numerical simulation method, we investigate the easiest liquid accumulation points and the liquid‐holding rate of wave‐shaped foam drainage pipelines, with factors such as inlet gas velocity, inlet liquid velocity, import and export differential pressure, undulation angle, and inlet temperature change rule. Among them, the error between the numerical simulation results and the experimental results is 4.68%. Finally, after considering the influence of the aforementioned factors on the liquid retention rate of wave‐shaped pipelines, a new liquid retention rate calculation model for wave‐shaped pipelines with foam drainage is established by introducing dimensionless numbers, such as gas‐phase velocity coefficient, liquid‐phase velocity coefficient, and angle correction coefficient. The method is compared with the results of previous research, and the error is within 15%. The model has a simple form and high calculation accuracy, providing a theoretical basis for pipeline inspectors to predict liquid accumulation conditions and reasonably adjust production schedules. [ABSTRACT FROM AUTHOR]

Because oil and gas pipelines reside in high-temperature, high-pressure and highly acidic environments for a long time, it is very common for such pipes to experience corrosion thinning. To solve the long-term online monitoring problem of piezoelectric ultrasonic dry coupling of monitored objects with different surface roughnesses, the effects of different thicknesses of silver plates, different surface roughnesses and different coaxial loads on piezoelectric ultrasonic dry coupling were studied here. To improve the low SNR of the acquired signal, a Batworth high-pass filter and zero-phase digital filter are proposed for online ultrasonic monitoring. The effects of three kinds of roughness and axial load on the piezoelectric ultrasonic dry coupling signal are studied, and the relationship between the roughness, thickness of the silver plate and axial load is obtained. The results show that under different roughness conditions, the SNR of the ultrasonic signal increases with increasing axial load. When the axial load reaches a certain magnitude, the SNR of the ultrasonic signal tends to be stable. When the surface roughness is Ra = 1.6 µm and the thickness of the silver plate is 0.05 mm, the SNR of the ultrasonic signal reaches the best value, and the required axial load is minimal. [ABSTRACT FROM AUTHOR]

Gas dehydration plays a critical role in gas refining processes due to the potential problems caused by the presence of water vapor. The inclusion of water vapor can lead to issues such as hydrate formation, pressure drop, and pipeline corrosion. In this research, a deep eutectic solvent (DES) absorbent was employed to absorb water vapor and subsequently, its absorption performance was compared with the absorption of tri-ethylene glycol (TEG) and lithium chloride, the most commonly used absorbents in water vapor separation processes. To do so, the influence of several effective parameters, including the inlet air flow rate, different ratios of choline chloride to urea (ChCl:Urea), the weight percentage of liquid water in the absorbent, and the viscosity of DES were investigated. The results demonstrated that DES is highly efficient for water vapor separation, outperforming both TEG and aqueous lithium chloride solutions. Moreover, increasing the inlet air flow rate was found to decrease absorption recovery due to reduced residence time. Additionally, a ChCl ratio of 1:2 yielded the highest absorption efficiency. [ABSTRACT FROM AUTHOR]

In response to China's dual carbon call, the petroleum industry is committed to green transformation, promoting the energy green revolution, focusing on domestic offshore CO2 -enriched oil and gas reservoirs, and carrying out offshore platform carbon capture, utilization, and storage–enhanced oil recovery (CCUS-EOR) pilot projects. CO2 continuously displaces crude oil while being injected into deep-sea oil and gas reservoirs for carbon sequestration, achieving an increase in oil recovery and residual oil recovery. However, the implementation of offshore CCUS-EOR technology relies on the safe transportation of supercritical CO2 pipelines. Due to the unique physical and chemical properties of supercritical CO2 , the safe transportation of supercritical CO2 pipelines faces multiple threats. This paper focuses on the current status of safe transportation technology for supercritical CO2 pipelines on offshore platforms, and summarizes multiple operational challenges, including obtaining high CO2 gas sources, high construction costs of pipelines, complex phase change of media, and internal and external corrosion of pipelines. The risk factors for failure of supercritical CO2 pipelines on offshore platforms were systematically identified, and the mechanism of leakage hazards of supercritical CO2 pipelines was determined. Based on the six-step cycle of pipeline integrity management, a targeted integrity management method for supercritical CO2 pipelines on offshore platforms is proposed, providing reference for improving the safety transportation technology system of supercritical CO2 pipelines on offshore platforms. [ABSTRACT FROM AUTHOR]

Microbial corrosion of X60 pipeline steel was examined by polarization scan, electrochemical impedance spectroscopy, scanning electron microscopy, x-ray diffractometry, and energy dispersive spectroscopy during and after immersion in a groundwater environment containing mixed colonies of anaerobic sulfate-reducing bacteria (SRB) and aerobic iron-oxidizing bacteria (IOB). The results show that individual SRB and IOB affected the electrochemical process of steel, and they also have a significant synergistic effect on intensifying microbial proliferation and promoting corrosion. IOB improved the metabolic activities of SRB by O2 consumption and biofilm formation, thus creating a suitable anaerobic environment for SRB and promoting localized corrosion. The corrosion process of the steel in SRB/IOB mixed culture was influenced comprehensively by dissolved oxygen, steel/biofilm interactions, metabolic activities, and by-products. [ABSTRACT FROM AUTHOR]

Biogas desulphurisation plants aim to remove hydrogen sulphide and other gaseous compounds that occur in the gas mixture. This mainly concerns the reduction of H2S which reacts with most metals such as iron or copper, which leads to the corrosion of pipelines and equipment. The aim of this research was to use two materials to adsorb hydrogen sulphide from biogas and to compare the efficiency of these two processes. Biogas was passed through both adsorbents. The concentration of hydrogen sulphide was measured upstream and downstream of the adsorbent bed. The results are summarised in diagrams. The first material used in the biogas desulphurisation plant at the wastewater treatment plant was bog iron ore. The bed was replaced several times during the year to maintain the efficiency of hydrogen sulphide removal from the biogas. After a year, a new adsorbent called "SulfurE" was used in place of the bog iron ore. The new bed operated with higher efficiency than the bog iron ore. The operating period between bed replacements was also extended. The bog iron ore bed in the desulphurisation plant was replaced on average 3 to 4 times a year, depending on the amount of hydrogen sulphide flowing into the desulphurisation plant (the more H2S, the higher the frequency of bed replacement). The bed in the desulphurisation plant filled with the "SulfurE" product operated for about 9 months with 90% hydrogen sulphide absorption efficiency (depending on the quality of biogas produced). [ABSTRACT FROM AUTHOR]

Microbial corrosion is the deterioration of materials associated with microorganisms in environments, especially in oil- and gas-dominated sectors. It has been widely reported to cause great losses to industrial facilities such as drainage systems, sewage structures, food-processing equipment, and oil and gas facilities. Generally, bacteria, viruses, and other microorganisms are the most important microorganisms associated with microbial corrosion. The destructive nature of these microorganisms differs based on the kind of bacteria involved in the corrosion mechanism. Amongst the microorganisms related to microbial corrosion, sulfate-reducing bacteria (SRB) is reported to be the most common harmful bacteria. The detailed mechanistic explanations relating to the corrosion of pipelines by sulfate-reducing bacteria are discussed. The mechanism of microbial corrosion in pipelines showing the formation of pitting corrosion and cathodic depolarization is also reported. The current review provides theoretical information for the control and protection of pipelines caused by microbial corrosion and how new eco-friendly protection methods could be explored. [ABSTRACT FROM AUTHOR]

The impact of Flavin adenine dinucleotide (FAD) on sulfate-reducing bacteria (SRB) corrosion of a pipeline welded joint (WJ) was investigated under anaerobic condition in this paper. The results showed that the thickness of the corrosion product on heat affected zone (HAZ) was lower than that on base metal (BM) and welded zone (WZ), and the FAD addition enhanced the development of the protruding microbial tubercles on the WJ. The local corrosion degrees of the BM and WZ coupons were significantly higher than that of the HAZ coupon. Besides, the FAD addition simultaneously promoted local corrosion of all three zones of the WJ in the SRB inoculated environment, and the promotion role was much more pronounced on the WZ coupons. The selective promotion effect of FAD on SRB corrosion in the WJ was attributed to the special structure of the WZ, the selected SRB attachment and the FAD/FADH2 redox feedback cycle. [ABSTRACT FROM AUTHOR]

Carbon capture, utilization, and storage (CCUS) technologies are crucial for reducing CO2 emissions. Currently, subsea CO2 storage is considered a highly feasible CCUS method. With the development of marine CCUS projects, impact loads from ship anchoring and marine debris, combined with internal corrosion defects in CO2 transport pipelines, significantly increase the risk of pipeline failure. This represents a major challenge for offshore SCCO2 pipelines. To investigate the stress–strain response of corroded pipelines under impact loads, a pipeline model with corrosion defects under rockfall impact conditions was established using ABAQUS 2014 finite element software. By varying factors such as the rock mass, impact velocity, drop point, and defect area, a single-variable analysis was conducted to explore the dynamic response of the pipeline. The results indicate that the rock mass and impact velocity are the key factors affecting pipeline stress, while the drop point and defect area have minimal impacts. Additionally, when the pipeline reaches yield failure, the effects of these factors become negligible. [ABSTRACT FROM AUTHOR]

This paper employs the Finite Element Method (FEM) to simulate and analyze the effects of corrosion defect parameters on the stress and failure pressure of pipelines. It investigates how the boundary conditions of the pipeline model influence stress and examines the sensitivity of failure pressure to corrosion defect parameters. A nonlinear regression equation has been developed from a dataset obtained through simulation experiments to predict the failure pressure of corroded pipelines. To validate the effects of corrosion defect parameters on failure pressure, a hydrostatic test platform for an API 5L X65 pipeline with corrosion defects was established to measure stress levels and failure pressures across varying corrosion defects. This study reveals that failure pressure is negatively correlated with corrosion length and depth, while positively correlated with corrosion width. Among these parameters, corrosion depth exerts a more significant influence on the pipeline's failure pressure than corrosion length and width. Within the range of corrosion defect parameters examined, the maximum deviation of the prediction equation's results from the simulation results is 8.71%, with an average deviation of 5.81%. The standard deviation of the fitted residuals is 0.01837. Additionally, the maximum deviation between the predicted results and experimental measurements is 8.39%, with an average deviation of 7.77%. The strong agreement between the predicted results from the equation and the actual measured data underscores the effectiveness of the nonlinear regression equation. [ABSTRACT FROM AUTHOR]

The mechanism causing the dramatic intensification of the corrosion deterioration of carbon steel pipes in a crude oil storage facility has been investigated. This study considers a number of factors affecting corrosion in crude oil, such as the water content, the corrosivity of the aqueous phase, the kinetics of water–oil separation, the effect of dissolved oxygen, the effect of the crude oil quality, the degree of stagnancy inside of the pipes, the possible contribution of microbially induced corrosion (MIC) and the presence of deposits. The key root of the corrosion intensification was the separation of the water phase, supported by stagnancy, which eventually led to the formation of stable shallow pits surrounded by cathodic areas. [ABSTRACT FROM AUTHOR]

As a critical component in industrial production, pipelines face the risk of failure due to long-term corrosion. In recent years, acoustic emission (AE) technology has demonstrated significant potential in online pipeline monitoring. However, the interference of flow-induced noise seriously hinders the application of acoustic emission technology in pipeline corrosion monitoring. Therefore, a pattern-recognition model for online pipeline AE monitoring signals based on blind source separation (BSS) and a convolutional neural network (CNN) is proposed. First, the singular spectrum analysis (SSA) was employed to transform the original AE signal into multiple observed signals. An independent component analysis (ICA) was then utilized to separate the source signals from the mixed signals. Subsequently, the Hilbert–Huang transform (HHT) was applied to each source signal to obtain a joint time–frequency domain map and to construct and compress it. Finally, the mapping relationship between the pipeline sources and AE signals was established based on the CNN for the precise identification of corrosion signals. The experimental data indicate that when the average amplitude of flow-induced noise signals is within three times that of corrosion signals, the separation of mixed signals is effective, and the overall recognition accuracy of the model exceeds 90%. [ABSTRACT FROM AUTHOR]

ABSTRACT As an important infrastructure for oil and gas transportation, the safe and stable operation of long‐distance pipelines is significant for guaranteeing national energy security and economic development. However, pipelines are susceptible to corrosion due to various factors. Therefore, it is crucial to take effective corrosion protection measures. Pulse current cathodic protection technology, as an advanced pipeline corrosion protection technology, is superior to traditional cathodic protection technology. This paper mainly summarizes the research progress of pulse current cathodic protection technology for long‐distance pipelines in recent years. It briefly discusses the protection mechanism, characteristic parameters, challenges, and development trends of pulse current cathodic protection technology, which provides a useful reference for the further promotion and application of pulse current cathodic protection technology for long‐distance transport pipelines. [ABSTRACT FROM AUTHOR]

Microbiologically influenced corrosion (MIC) caused by sulfate‐reducing bacteria (SRB) is a major threat to buried pipelines. The crevices beneath disbonded coatings provide the environment for the survival and growth of SRB, accelerating the attachment of SRB and significantly reducing the effectiveness of buried pipelines. In this work, the influence of initial pH values (6.4, 8.0) and SRB concentrations (2.0 × 101, 4.5 × 102, 2.5 × 103 cells/mL) were investigated on the behaviors of L415 carbon steel. The results indicated that the overall uniform corrosion rate of L415 carbon steel decreased while the maximum pitting corrosion rate exhibited an increasing trend with the increasing of initial concentration of SRB. In comparison to the pH 6.4 environment, the overall risk of pitting corrosion in pH 8.0 environment was reduced due to the biomineralization of SRB, enhancing the protection of metal materials. [ABSTRACT FROM AUTHOR]

Rod-type metal corrosion probes based on electromechanical impedance (EMI) technique can quantitatively assess the amount of corrosion, which have a promising application in pipeline corrosion monitoring and have received much more attention. In the field of structural health monitoring, the EMI technique based on series and parallel connections has been widely studied and is very promising, but it is yet to be used in the probe design. In this work, a kind of novel metal corrosion probe with two piezoelectric elements in series and parallel connections was proposed, and its performance was investigated comprehensively by combining theoretical analysis with experiment research. Theoretical models of the proposed probe in the longitudinal vibration mode for both series and parallel connections were established, and verified by the experimental results. Influences of the thicknesses of piezoelectric layer and ceramic layer on the probe performance were analyzed. Artificial quantitative corrosion tests and accelerated corrosion tests were designed to evaluate the quantitative corrosion monitoring capacity. Temperature sensitivity tests were conducted to study the temperature dependence. The wireless impedance measurement was performed to confirm the online monitoring ability. Comparisons for the probe performance between the series and parallel connections were also presented. This work provided a comprehensive understanding for this kind of novel probe, which is beneficial to develop low-cost, high-precision, high-stability pipeline corrosion real-time monitoring technology. [ABSTRACT FROM AUTHOR]

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This paper introduces a literature review of the accomplished research to calculate the strain concentration factor which shall be considered during the concrete coated subsea pipelines design. The strain concentration results from the discontinuity of the concrete coating which is applied to pipe joints to enhance the pipeline stability on the seabed. The paper introduces a definition of the strain concentration factor and a conclusive explanation of the work performed to calculate the strain concentration factor using the following three methods: full-scale tests, analytical models, and numerical models. The paper also introduces other works addressing the contribution of concrete coating to pipe stiffness. Literature indicates that while full-scale tests produce the most accurate values for the strain concentration factor, due to cost implications, the method is limited to a small range of pipe sizes and coating properties. Although the analytical method produces acceptable results, prediction of strain concentration factor due to concrete coating sliding and beyond steel yield stress and concrete crushing limit is unpredictable. The numerical method using finite element (FE) analysis indicates acceptable strain concentration factor values, however, careful consideration shall be taken due to possible modelling inaccuracies. The review shows that the strain concentration factor is mainly influenced by the thickness and strength of the concrete coating as well as the shear capacity of the external corrosion coating, whilst due to its low impact, the effect of the concrete coating reinforcement is not considered for most of the analysis due to low significance. [ABSTRACT FROM AUTHOR]

Accurately assessing the residual strength of corroded oil and gas pipelines is crucial for ensuring their safe and stable operation. Machine learning techniques have shown promise in addressing this challenge due to their ability to handle complex, non-linear relationships in data. Unlike previous studies that primarily focused on enhancing prediction accuracy through the optimization of single models, this work shifts the emphasis to a different approach: stacking ensemble learning. This study applies a stacking model composed of seven base learners and three meta-learners to predict the residual strength of pipelines using a dataset of 453 instances. Automated hyperparameter tuning libraries are utilized to search for optimal hyperparameters. By evaluating various combinations of base learners and meta-learners, the optimal stacking configuration was determined. The results demonstrate that the stacking model, using k-nearest neighbors as the meta-learner alongside seven base learners, delivers the best predictive performance, with a coefficient of determination of 0.959. Compared to individual models, the stacking model also significantly improves generalization performance. However, the stacking model's effectiveness on low-strength pipelines is limited due to the small sample size. Furthermore, incorporating original features into the second-layer model did not significantly enhance performance, likely because the first-layer model had already extracted most of the critical features. Given the marginal contribution of model optimization to prediction accuracy, this work offers a novel perspective for improving model performance. The findings have important practical implications for the integrity assessment of corroded pipelines. [ABSTRACT FROM AUTHOR]

The hazard of stray current attracts more and more attention due to the potential infrastructure failure caused by the electrochemical corrosion. In view of the poor insulation performance and lack of stray current collection system in the metro depot, stray current leakage becomes particularly evident in this area. In order to evaluate the corrosion risk of buried metal pipeline surrounding metro depot, an assessment model for interference scope induced by stray current is proposed in this paper. The distribution of stray current is calculated based on the resistive network by considering different boundary conditions in different areas of metro depot, and the interference scope is assessed by surface potential gradient for corrosion risk of corroded pipeline. Moreover, the characteristics of surface potential gradient distribution in different areas of metro depot and the influence of electrical parameters are analyzed. Finally, the proposed model is verified through simulation and experimental results. [ABSTRACT FROM AUTHOR]

The problem of corrosion in oil and gas pipelines is one of the major factors affecting the process safety and efficient sustainability development of the oil and gas industry. To gain a better understanding of global research trends and dynamics in the field of oil and gas pipeline corrosion and to advance the development of corrosion control technology, we conducted a literature review using a sample of 1,745 papers from the Web of Science (WOS) database published from 2002 to 2022. We employed a bibliometric analysis approach employed to investigate the distribution of publications over time, geographic regions, major organizations, major authors, journal cocitation, and literature cocitation, and to identify research hotspots and frontiers. The results revealed an exponential growth in the overall number of papers, with the most rapid increase occurring in the last 4 years. China, the US, Canada, the United Kingdom, and Brazil emerged as the most active countries in oil and natural gas pipeline corrosion research, and Mexico, Canada, and Australia also exhibited significant influence in the field. The journals Engineering Failure Analysis, Corrosion, and Corrosion Science had the highest number of publications and impact in this domain. Notably, Corrosion Science stood out as the most influential and highly regarded journal in the corrosion field. The fundamental theories and research framework in the realm of oil and natural gas pipeline corrosion have been primarily established, and a large number of research directions and frontier branches are emerging. The impact of flow parameters on corrosion, pipeline reliability assessment, and analysis of corrosion defects and failures are identified as the three main development paths in this field. In terms of research methodologies, machine learning techniques are becoming increasingly prevalent, with a growing number of studies adopting various machine learning methods. Among these methods, explainable deep learning is at the forefront of development in the field of oil and natural gas pipeline corrosion. [ABSTRACT FROM AUTHOR]

In engineering applications, the simultaneous suspension and corrosion of pipelines under unstable geological conditions present significant challenges, leading to large deformations, stress concentrations, and potentially catastrophic failures. Previous research often overlooked the simultaneous impact of these factors, resulting in inaccuracy in the failure analysis and further maintenance strategies. To fill the gap, this paper employs numerical analysis to create and simulate a series of pipe–soil coupling models uniquely considering internal corrosion for a more precise investigation of mechanical and failure behaviors in high-strength spanning pipelines. This research pioneers a comprehensive parametric analysis, exploring key factors such as operating conditions and geometric features on deformation, stress, strain, and stress concentration factor (SCF), all vital for failure determination. The results offer crucial insights, showing that maximum stresses in corroded spanning pipelines occur within the corrosion area, unlike in intact pipelines, where they typically appear at the span end. Increases in spanning length, corrosion dimensions, and internal pressure lead to upward trends in the maximum longitudinal stress, strain, and vertical displacement. The axial location of the internal corrosion also significantly affects the pipeline's mechanical state. The longitudinal strain escalates along the axial location, being 1.97 times smaller at 2/10ls compared with 5/10ls. This study diverges from standard analyses by innovatively spotlighting the significant impact of corrosion width on spanning pipeline safety, particularly affecting longitudinal SCF. Maximum SCF increases by 36.1% with the corrosion width expanding from 5° to 50°, showcasing a more pronounced effect than that of corrosion length. This study advances pipeline integrity knowledge and lays the groundwork for future research, offering crucial tools for life span prediction and failure prevention in spanning pipelines. Practical Applications: Our study reveals a more accurate way to simulate and predict when and where pipelines might fail due to the combination of internal corrosion and spanning. Traditionally, it was thought that the ends of suspended pipelines were most at risk, but our research shows the weak spots are within the corrosion area. The obtained stress concentration factor can be further used to estimate the fatigue life of a spanning pipeline. The simulation results also suggest that corrosion width is vital for spanning pipelines' mechanical behaviors. [ABSTRACT FROM AUTHOR]

When traversing through an active strike-slip fault, buried pipelines may be subjected to permanent ground deformation (PGD), causing large strains in the pipeline during an earthquake. The presence of bends near the fault-crossing zones may further increase the strain in the pipe. Moreover, it is well acknowledged that bends are the most vulnerable location to earthquake damage, mainly when compressive strain develops due to PGD. Hence, most design guidelines recommend constructing pipelines without field bends, elbows, and flanges crossing the fault zone. However, it is not always possible to provide only a straight segment of the pipeline, especially for blind faults where the location of the faults is unknown. Hence, the present study aims to investigate the response of buried continuous steel pipelines with field bends subjected to strike-slip faulting by conducting an extensive parametric study. A three-dimensional pipe-soil interaction model is developed in a finite element framework for this study. The pipeline response in terms of its maximum von-Mises stress and maximum longitudinal stress and strain due to fault crossing is studied for various influencing parameters such as pipe bend angle, soil strength, pipe burial depth, and distance of the fault trace from the bend. Based on the results obtained, suitable relationships in terms of modification factors over the response of a straight pipeline as a function of a few critical parameters are determined using regression analyses. It is concluded that providing bends to the pipeline can significantly affect its structural response when subjected to fault displacement when the fault trace is close to the pipe bend. The primary outcome of this investigation would be to suggest a simplified methodology to estimate the response of pipelines having field bends while crossing fault lines from the response of straight pipelines in a similar scenario. [ABSTRACT FROM AUTHOR]

The corrosion mechanism of L245NS steel and L360QS steel of gas injection/withdrawal pipeline of underground gas storage in different acidic gas environments was studied by means of SEM, EDS, XRD, XPS, and GC-MS. The results show that Fe2O3, Fe3O4, and CaCO3 with poor protection were formed on the surface of L245NS steel, which provided a channel for the corrosive medium to contact the surface of the metal matrix and accelerated the corrosion rate of the pipeline. Meanwhile, CI− had a small radius and strong penetrability, which was easy to pass through the product film to reach the surface of the metal matrix to participate in the reaction, resulting in corrosion defect pits. The inner wall of L360QS steel was attached with gum, forming a dense protective film on the inner surface of the pipeline, and it was difficult for corrosive substances to enter the metal matrix, which played a role in inhibiting the corrosion of the pipeline. [ABSTRACT FROM AUTHOR]

Pipeline transportation is the main means of transportation of oil, natural gas and other energy sources. During transportation, corrosive substances in oil and natural gas can cause damage to the pipeline structure. A non-destructive testing technology for pipeline corrosion based on electromagnetic ultrasound technology was proposed to improve the stability and safety of energy pipeline transportation systems. This technology utilized empirical mode decomposition and singular spectrum analysis to denoise electromagnetic ultrasound signals. The designed electromagnetic signal denoising algorithm completely removed mild noise pollution. When using this method to detect pipeline corrosion, the maximum calculation error of pipeline wall thickness was 0.1906 mm, and the lowest was 0.0015 mm. When detecting small area corrosion deficiency, the amplitude of the detection signal increased with the depth, up to a maximum of around 24 V, which accurately reflected small area defects. This non-destructive testing technology for pipelines can effectively detect the pipeline corrosion, which is helpful for the regular maintenance of pipeline energy transmission systems. [ABSTRACT FROM AUTHOR]

Pipelines are an important transportation form in industry. However, pipeline corrosion, particularly that occurring internally, poses a significant threat to safe operations. To detect the internal corrosion of a pipeline, a method utilizing piezoelectric sensors alongside singular spectrum analysis is proposed. Two piezoelectric patches are affixed to the exterior surface of the pipeline, serving the roles of an actuator and a sensor, respectively. During the detection, the signals excited by the actuator are transmitted through the pipeline's wall and are received by PZT2 through different paths, and the corresponding piezoelectric sensor captures the signals. Then, the response signals are denoised by singular spectrum analysis, and the first several wave packets in the response signals are selected to establish a feature for pipeline corrosion detection. At last, the envelope area of the selected packets is calculated as a feature to detect corrosion. To validate the proposed method, corrosion monitoring experiments are performed. The experimental results indicate that the envelope area of the first several wave packets from the response signals, following singular spectrum analysis, can serve as a feature to assess the degree of pipeline corrosion, and the index has a monotonic relationship with the corrosion depth of the pipeline. This method provides an effective way for pipeline corrosion monitoring. [ABSTRACT FROM AUTHOR]

Buried pipelines are widely used, so it is necessary to analyze and study their fracture characteristics. The locations of corrosion defects on the pipe are more susceptible to fracture under the influence of internal pressure generated during material transportation. In the open literature, a large number of studies have been conducted on the failure pressure or residual strength of corroded pipelines. On this basis, this study conducts a fracture analysis on buried pipelines with corrosion areas under seismic loads. The extended finite element method was used to model and analyze the buried pipeline under seismic load, and it was found that the stress value at the crack tip was maximum when the circumferential angle of the crack was near 5° in the corrosion area. The changes in the stress field at the crack tip in the corrosion zone of the pipeline under different loads were compared. Based on the BP algorithm, a neural network model that can predict the stress field at the pipe crack tip is established. The neural network is trained using numerical model data, and a prediction model with a prediction error of less than 10% is constructed. The crack tip characteristics were further studied using the BP neural network model, and it was determined that the tip stress fluctuation range is between 450 MPa and 500 MPa. The neural network model is optimized based on the GA algorithm, which solves the problem of convergence difficulties and improves the prediction accuracy. According to the prediction results, it is found that when the internal pressure increases, the corrosion depth will significantly affect the crack tip stress field. The maximum error of the optimized neural network is 5.32%. The calculation data of the optimized neural network model were compared with the calculation data of other models, and it was determined that GA-BPNN has better adaptability in this research problem. [ABSTRACT FROM AUTHOR]

In view of the problems of frequent leakage and corrosion failure in a gathering and transportation pipeline in Jiyuan Oilfield, water quality analysis, corrosion and scaling product analysis, surface morphology and element composition analysis were carried out. The corrosion mechanism under multi-media environment of CO2, H2S, dissolved oxygen, Cl and scaling ions was studied, and the corrosion and scaling treatment methods were optimized. The results show that the main factors causing pipeline corrosion are CO2-H2S-Cl- co-existing corrosion and bacterial corrosion, which promote the development of local corrosion. By new corrosion inhibitor and coating combined anti-corrosion technology, the on-site corrosion rate is reduced to 0.001 8 mm/a, which can minimize or reduce the corrosion of gathering and transportation pipelines, and extend its service life. [ABSTRACT FROM AUTHOR]

The concrete composition of different pipelines varies greatly, and a comprehensive analysis of the impact of concrete design on pipeline corrosion is required. Developed an integrated model based on Scikit-Optimize, XGBoost and SHAP to analyze concrete's carbonation and sulfuric acid resistance from five aspects: binder type, supplementary cementitious material (SCM's), aggregate, admixture and w/b. Choose Scikit-Optimize for parameter optimization. As an explanation model, the SHAP model can perform analysis well and explain the analysis basis of the XGBoost training model. The established model can accurately predict the corrosion effect (R2 >0.987) without overfitting. Binder should be maintained at 380 to 400 (kg/m3). Water/binder and coarse aggregate/binder are the two main factors that influence the binder, and they should be maintained at a ratio of around 0.4 to 0.6 and 2.5, respectively. Fly ash (FA) should be SCM's used as at a range of 300 to 350 (kg/m3) to improve corrosion resistance. [ABSTRACT FROM AUTHOR]

The solvent method for CO2 capture has the advantages of mature technology and low cost, and is widely used. As commonly used absorbents, organic amines have the advantages of fast absorption rate and large absorption capacity. However, due to the chemical reaction between organic amines and CO2, the solution becomes corrosive, resulting in corrosion of equipment pipelines. The corrosion mechanism of organic amine solutions was reviewed. Hydrogenated amine ions, bicarbonate ions and water molecules are the main oxidants, which provide conditions for the occurrence of corrosion. The effects of the types and concentrations of organic amine solution, CO2 loadings, temperatures, O2 content and degradation products on the corrosiveness of the solution were discussed. Among them, CO2 loadings and temperatures are the main factors. The methods of using inorganic and organic corrosion inhibitors, adjusting the pH value of the solution and using stainless steel materials were summarized. The organic corrosion inhibitors for amine solutions are more worthy value of attention. The development direction of future corrosion inhibition technology was put forward. It is necessary to develop new corrosion inhibitors and combine them with corrosion resistant materials, which can provide a reference for further research and solving the corrosion problem of organic amine solutions. [ABSTRACT FROM AUTHOR]

Microbiologically influenced corrosion (MIC) has long been a critical issue due to its potential to cause severe damage to equipment and the associated risk of operational failures, leading to significant financial losses. This study investigates the resistance to MIC caused by sulfate-reducing bacteria (SRB) in four types of pipeline steel materials, which are soon to be introduced to the market. Two of these materials have been alloyed with copper during the metallurgical process. The uniform corrosion rates of the copper-alloyed materials were found to be 0.012 ± 0.002 mm/y, 0.060 ± 0.01 mm/y, and 0.010 ± 0.001 mm/y under test conditions of 25 °C, 40 °C, and 60 °C, respectively. In contrast, the unalloyed steels exhibited corrosion rates of 0.370 ± 0.033 mm/y, 0.060 ± 0.01 mm/y, and 0.378 ± 0.032 mm/y, respectively. The data indicate that the copper-alloyed materials demonstrate superior resistance to MIC, as confirmed by corrosion morphology, weight loss measurements, and electrochemical data. These findings suggest that copper alloying can significantly enhance the MIC resistance of steel materials, offering a promising direction for future material development. [ABSTRACT FROM AUTHOR]

Sulfate-reducing bacteria (SRB) are the primary cause of corrosion in oil and gas pipeline steel. To understand how temperature and immersion time affect the SRB-induced corrosion of BG L450OQO-RCB pipe steel, the present study delved into the morphology and elemental composition of corrosion products, corrosion rate, corrosion solution composition, and electrochemical performance at different temperatures (25, 40, and 60 °C) and immersion times (5, 10, and 20 days). During the SRB corrosion of the investigated steel, extracellular polymeric substances (EPSs), iron sulfide, and iron phosphide were produced on the surfaces of the steel samples, along with the calcium carbonate product. Chloride ions in the corrosion solution contributed to the corrosion of steel and the formation of chlorides on steel surfaces. Over time, the quantities of EPSs, iron sulfide, and iron phosphide gradually decreased with immersion time. The presence of surface iron chloride initially increased and then decreased with immersion time. Conversely, the presence of calcium carbonate surface product initially decreased and then increased with immersion time. The content of SRB extracellular polymer, iron sulfide, and iron phosphide changed imperceptibly between 25 and 40 °C, but the overall content decreased at 60 °C. The content of surface ferric chloride remained practically unchanged between 25 and 40 °C but increased at 60 °C. The calcium carbonate surface product increased slightly with higher temperature. The corrosion of Cu-containing steel by SRB follows the cathodic depolarization theory. [ABSTRACT FROM AUTHOR]

Pipeline transportation is an economical and effective way for transferring carbon dioxide (CO2) to the sea, serving as a key procedure for an offshore carbon capture, utilization and sequestration (CCUS) project, as well as a core technology for the large-scale construction of CCUS projects in China. This study clarifies the advantages of China in the construction of offshore CCUS projects, typical offshore carbon pipeline scenarios, and typical offshore CO2 transportation modes. It also reviews the technologies and projects in China and abroad regarding offshore CO2 transportation via pipelines. The current technologies relevant to offshore CO2 pipeline transportation are systematically reviewed. Specifically, the process technologies include CO2 fluid state analysis and flow assurance; corrosion evaluation, monitoring, and early warning; real-time monitoring of pipe leakage; and release of high-pressure CO2 and its environmental impacts. The material technologies include the fracture of pipeline materials and its mitigation, high corrosion-resistant and sealing materials, key corrosion-control techniques for the long-term operation of pipelines, and corrosion risk evaluation of CO2 injection wells. Further efforts should focus on the following aspects: material selection systems for the complex conditions during offshore CO2 pipeline transportation, full-chain intelligent management and digital twin technologies for CO2 pipelines, key technologies regarding the whole life-time operation of subsea CO2 pipelines, and evaluation and assurance techniques for the transferred transportation pipelines. Furthermore, the following suggestions are proposed to promote the high-quality development of the offshore CO2 pipeline transportation system in China: (1) promoting the planning of offshore CO2 pipeline networks, (2) expanding interdisciplinary innovations, (3) establishing standards systems that applicable to both onshore and offshore scenarios, and (4) encouraging the participation of diversified technology service enterprises.

Microstructure is an important factor affecting hydrogen diffusion in pipeline steels. Due to the different stress and heat conditions, the surface and internal microstructure of the rolled pipeline steels is different. The ferrite grain size in surface layer of X42 pipeline steel is smaller than other locations, while the surface layer of X52 pipeline steel has continuous banded ferrite/pearlite structure and grains with uneven size. Hydrogen permeation behavior is investigated at different positions in the normal direction of X42 and X52 pipeline steels using the electrochemical hydrogen permeation technique. The results show that the values of the effective diffusion coefficient of surface layer in X42 and X52 pipeline steels are the smallest, while the values of the subsurface hydrogen concentration at steady state are the largest. Hydrogen microprint experiment results indicate hydrogen atoms mainly escape at pearlite, ferrite grain boundaries and near inclusions in X42 and X52 pipeline steels. • The surface and interior microstructure of rolled pipeline steel is inconsistent. • Hydrogen diffusion is hindered by grain boundaries. • The continuous banded ferrite/pearlite structure impedes hydrogen diffusion. • Hydrogen atoms mainly escape at pearlite and ferrite grain boundaries. [ABSTRACT FROM AUTHOR]

To combat abiotic CO2 corrosion of pipelines, chromium steels (CrSs) are used to replace carbon steels, but CrSs can suffer very severe pitting corrosion caused by microbiologically influenced corrosion (MIC) because their passive films are not as good as those on high-grade stainless steels, and their MIC often involves (semi-)conductive corrosion product films. In this study, severe pitting corrosion (2.0 cm/a pitting corrosion rate) with a 7-day weight loss of 3.8 ± 0.5 mg/cm2 (0.26 mm/a uniform corrosion rate) was observed on 13Cr coupons incubated anaerobically with a highly corrosive pure-strain sulfate reducing bacterium (SRB) Desulfovibrio ferrophilus IS5 in 125 mL anaerobic vials filled with 50 mL enriched artificial seawater at 28°C. A popular green biocide, namely tetrakis hydroxymethyl phosphonium sulfate (THPS), was enhanced by biofilm dispersing Peptide A (a 14-mer) to mitigate SRB MIC against 13Cr. The 7-day weight losses for coupons with 50 ppm (w/w) THPS, 50 ppm THPS + 100 nM (180 ppb) Peptide A and 100 ppm THPS were reduced to 2.2 ± 0.2 mg/cm2, 1.5 ± 0.5 mg/cm2, and 0.3 ± 0.2 mg/cm2, respectively. The pitting rates also decreased from 20 mm/a to 12 mm/a, 8.6 mm/a, and 1.5 mm/a, respectively based on the maximum pit depth data for the 7-day incubation. Electrochemical tests using a miniature electrochemical glass cell design supported the weight loss trend with additional transient corrosion rate information. THPS was found to be effective in mitigating severe pitting corrosion on 13Cr, and the enhancement effect of Peptide A for THPS was manifested. This work has significant implications in field applications when CrSs are considered as metal choices to replace carbon steels to combat abiotic CO2 corrosion in pipelines. When SRB MIC is a possible threat, a mitigation plan needs to be implemented to prevent potentially very severe pitting that can lead to pinhole leaks. [ABSTRACT FROM AUTHOR]

Evaluating the seismic resilience (SR) of water distribution systems (WDSs) can support decision-making in optimizing design, enhancing reinforcement, retrofitting efforts, and accumulating resources for earthquake emergencies. Owing to the complex geological environment, buried water supply pipelines exhibit varying degrees of corrosion, which worsens as the pipelines age, leading to a continuous degradation of their mechanical and seismic performance, thereby impacting the SR of WDSs. Consequently, this study proposes an SR evaluation method for WDSs that takes into account the corrosive environment and the service age of buried pipelines. Utilizing the analytical fragility analysis method, this research establishes seismic fragility curves for pipelines of various service ages and diameters in diverse corrosive environments, in combination with the Monte Carlo simulation method to generate seismic damage scenarios for WDSs. Furthermore, the post-earthquake water supply satisfaction is utilized to characterize the system performance (SP) of WDSs. Two repair strategies are employed for damaged pipes: assigning a single repair crew to address damages sequentially and deploying a repair crew to each damage location simultaneously, to assess the minimum and maximum SR values of WDSs. The application results indicated that the maximum decrease in SP across 36 conditions was 32%, with the lowest SR value of WDSs being 0.838. Under identical seismic intensities, the SR value of WDSs varied by as much as 16.2% across different service ages and soil conditions. Under rare earthquake conditions, the effect of the corrosive environment significantly outweighs the impact of service age on the SP of WDSs. Post-disaster restoration resources can minimize the impact of the corrosive environment and service age on the SR of WDSs. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study on data preprocessing and modeling for predicting corrosion in water pipelines of a steel industrial plant. The use case is a cooling circuit consisting of both direct and indirect cooling. In the direct cooling circuit, water comes into direct contact with the product, whereas in the indirect one, it does not. In this study, advanced machine learning techniques, such as extreme gradient boosting and deep neural networks, have been employed for two distinct applications. Firstly, a virtual sensor was created to estimate the corrosion rate based on influencing process variables, such as pH and temperature. Secondly, a predictive tool was designed to foresee the future evolution of the corrosion rate, considering past values of both influencing variables and the corrosion rate. The results show that the most suitable algorithm for the virtual sensor approach is the dense neural network, with MAPE values of (25 ± 4)% and (11 ± 4)% for the direct and indirect circuits, respectively. In contrast, different results are obtained for the two circuits when following the predictive tool approach. For the primary circuit, the convolutional neural network yields the best results, with MAPE = 4% on the testing set, whereas for the secondary circuit, the LSTM recurrent network shows the highest prediction accuracy, with MAPE = 9%. In general, models employing temporal windows have emerged as more suitable for corrosion prediction, with model performance significantly improving with a larger dataset. [ABSTRACT FROM AUTHOR]

The paper introduces a computer vision methodology for detecting pitting corrosion in gas pipelines. To achieve this, a dataset comprising 576,000 images of pipelines with and without pitting corrosion was curated. A custom-designed and optimized convolutional neural network (CNN) was employed for binary classification, distinguishing between corroded and non-corroded images. This CNN architecture, despite having relatively few parameters compared to existing CNN classifiers, achieved a notably high classification accuracy of 98.44%. The proposed CNN outperformed many contemporary classifiers in its efficacy. By leveraging deep learning, this approach effectively eliminates the need for manual inspection of pipelines for pitting corrosion, thus streamlining what was previously a time-consuming and cost-ineffective process. [ABSTRACT FROM AUTHOR]

X70 steel gas transmission pipeline has a large market share and a long operation time, and the problem of pipeline integrity, represented by corrosion, is now becoming increasingly prominent. Under actual working conditions, the corrosion of gas transmission pipelines is complex. In order to study the corrosion characteristics of X70 steel gas transmission pipeline under different soil environments, help pipeline integrity management and ensure operational safety, the raw gas pipeline of an LNG project was used as the object of study, and firsthand data were obtained with the help of OLYMPUS 38DL PLUS thickness gauge with the help of special hanging sheet deployment mode on site. The data were brought into a suitable gray prediction model to detect trends in condition data and to predict future corrosion levels. Finally, a sampling inspection plan with the best combination of time and cost was obtained. The results are as follows: 1. The trend in the corrosion data exhibits a typical single-peak sequence, coupled with the "S"-shaped growth characteristics of biological growth, which ultimately reveals that SRB is the main cause of pipeline corrosion; 2. Among the uncoated original state hangings, the greatest corrosion depths can be observed in 2018 and 2019, with the greatest change in corrosion depth in 2020. 3. The best Verhulst model is with cumulative corrosion depths of 249.00 μm and 250.61 μm for the next 2 years. The next step is to perform a full inspection of 50 uncoated original hanging pieces, while performing sampling inspection of 15 three-layer PE parcel pieces will improve the integrity of the pipeline. [ABSTRACT FROM AUTHOR]

This study integrated geographic information system (GIS) and remote sensing technology to identify areas around pipelines that are more susceptible to corrosion having the Kurdistan pipeline as a case study. Geospatial data are used to target factors such as rainfall, temperature, rivers, and minerals which increase the corrosion rate. Spatial data such as, the direction of slope, rainfall, proximity to rivers, and minerals, were collected and analyzed; maps were created for every individual factor to visualize their distribution. By overlaying these maps, regions that are at higher risk of corrosion were identified, which can be prioritized for further investigation or preventive measures. This paper's findings are significant for oil and gas industries, including pipeline operators and designers as corrosion can lead to devastating consequences. The novelty of this study is to identify areas along the pipeline at higher risk of corrosion through the application of geospatial information systems and remote sensing. This methodology holds immense potential for industries looking to proactively prevent corrosion through the implementation of preventative maintenance, monitoring programs, and the application of protective coatings and inhibitors. The results of this research demonstrate that environmental data, GIS, and remote sensing can predict corrosion in oil pipelines, offering valuable insights for better managing corrosion risk. [ABSTRACT FROM AUTHOR]

The paper presents the results of non‐destructive testing examinations, metallographic tests and risk assessment of degradation related to corrosion of amine regeneration unit in a desulphurisation system. Intensive corrosion resulting from acid gases environment upon water condensation causes perforation of the pipeline. Detailed analysis reveals cracking related to the mechanism of wet H2S. Hydrogen penetration, resulting from the wet H2S process, causes a decrease in mechanical properties of steel and an increase in hydrogen content inside steel. Corrosion results mostly from high stream velocity, the presence of acid gases (with high ammonia content), the presence of amine and low stream temperature. [ABSTRACT FROM AUTHOR]

In present study mass loss behaviour of base metal and heat-treated API X70 pipeline steel in different environments such as fresh water, sea water and sodium thiosulphate medium were observed for 50 days. Corrosion is the main failure in pipeline steel which need to be reduced with the use of suitable heat treatment process. In present study two heat treatment such as HT-1 900 °C (2 hour) with tempering at 450 °C (4 hour) and HT-2 800 °C (2 hour) with tempering at 450 °C (4 hour) was used. Mechanical, microstructure and corrosion rate of HT-1 and HT-2 specimen in different environments were observed. Maximum corrosion rate (0.306 mm/y) in fresh water while minimum corrosion rate (0.181 mm/y) in sodium thiosulphate medium was observed for base metal. Maximum corrosion rate (0.224 mm/y) in sodium thiosulphate while minimum corrosion rate (0.106 mm/y) in fresh water medium was observed for HT-1 specimen. For HT-2 specimen, Maximum corrosion rate (0.192 mm/y) in sea water while minimum corrosion rate (0.099 mm/y) in fresh water medium was observed. For HT-2 specimen, maximum average hardness of (30.3 HRC) in sea water while minimum average hardness of (28 HRC) of base metal was observed. In fresh water also HT-2 specimen, maximum average hardness is (26.3 HRC) while minimum average hardness of (24.6 HRC) of base metal was observed. After that maximum average hardness of base metal (26.6 HRC) in sodium thiosulphate while minimum average hardness of (21 HRC) of HT-2 specimen was observed. [ABSTRACT FROM AUTHOR]

Cathodic protection is a significant approach utilized to avoid the electrochemical corrosion of pipelines. This is accomplished by supplying an electric current to the structure that requires protection, such as a pipeline, from an external source. study aims to enhance the cathodic protection system by minimizing potential fluctuations along the pipeline hence preventing corrosion. It also aims to achieve economic feasibility by decreasing the number of anodes utilized. These objectives were accomplished by employing meta-heuristic optimization techniques. The present study involves formulating a mathematical model for a pipeline that provides fuel to the Al-Hilla 2 power plant in Iraq to assess the effectiveness of cathodic protection. Utilizing numerical simulation techniques, Multiphysics COMSOL, diverse scenarios are examined, resulting in the acquisition of substantial data. Subsequently, a neural network model is constructed using MATLAB. The primary factors influencing the distribution of cathodic protection potential are the numbers and positioning of the anodes and the output current. Subsequently, the optimization objectives involve determining the optimal anode number, position, and output current value by utilizing the Particle swarm organization (PSO) algorithm. The obtained results provide evidence that the proposed method holds a certain level of significance in guiding the design of cathodic protection systems. [ABSTRACT FROM AUTHOR]

This review article provides a comprehensive overview of the fundamentals, modelling approaches, experimental studies, and challenges associated with hydrogen gas flow in pipelines. It elucidates key aspects of hydrogen gas flow, including density, compressibility factor, and other relevant properties crucial for understanding its behavior in pipelines. Equations of state are discussed in detail, highlighting their importance in accurately modeling hydrogen gas flow. In the subsequent sections, one-dimensional and three-dimensional modelling techniques for gas distribution networks and localized flow involving critical components are explored. Emphasis is placed on transient flow, friction losses, and leakage characteristics, shedding light on the complexities of hydrogen pipeline transportation. Experimental studies investigating hydrogen pipeline transportation dynamics are outlined, focusing on the impact of leakage on surrounding environments and safety parameters. The challenges and solutions associated with repurposing natural gas pipelines for hydrogen transport are discussed, along with the influence of pipeline material on hydrogen transportation. Identified research gaps underscore the need for further investigation into areas such as transient flow behavior, leakage mitigation strategies, and the development of advanced modelling techniques. Future perspectives address the growing demand for hydrogen as a clean energy carrier and the evolving landscape of hydrogen-based energy systems. [Display omitted] • Hydrogen gas characteristics are useful to model flow in pipelines. • Flammability, embrittlement, and leak risks associated with hydrogen pose challenges in transportation. • Temperature variation and pressure drop across critical components are important aspects of pipeline design. [ABSTRACT FROM AUTHOR]

Utilizing the existing natural gas grid presents a promising method for transporting hydrogen on a large scale. However, the effects of natural gas and its impurities on hydrogen-assisted cracking in pipeline steel have not been adequately studied. This study aims to investigate the fatigue performance of X80 pipeline steel in hydrogen-enriched natural gas (HENG) environments and in mixtures containing the impurity CO 2. This is achieved through fatigue crack growth rate (FCGR) tests and density functional theory (DFT) calculations. The experimental results show that the FCGR in H 2 is slightly faster than that in HENG, whereas it is slower than that in the N 2 /CO 2 /H 2 mixtures. The enhanced FCGR by CO 2 further increases with the increasing CO 2 content. DFT computational results indicate that the adsorbed CO 2 on the iron surface significantly accelerates the migration of H atoms from surface to subsurface. This promotes the entry of hydrogen into the steel. [Display omitted] • CO 2 promotes fatigue crack growth rate of X80 in the hydrogen environment. • Fatigue crack growth rate further enhances with the increasing CO 2 content. • CO 2 has little effect on the H 2 adsorption and dissociation on the Fe(110). • CO 2 accelerates the surface H atom migration to the subsurface of the Fe(110). [ABSTRACT FROM AUTHOR]

X80 pipeline steel has played a vital role in oil and gas transportation in recent years. However, hydrogen-related issues frequently lead to pipeline failures during service, resulting in significant losses of properties and lives. Three heat treatment processes (furnace cooling (FC), air cooling (AC), and water cooling (WC)) were carried out to investigate the effect of different microstructures on hydrogen-induced cracking (HIC) susceptibility of X80 pipeline steel. The WC sample demonstrated the highest hydrogen embrittlement index, registering at 21.9%, while the AC and FC samples exhibited progressively lower values of 15.45% and 10.98%, respectively. Under equivalent hydrogen charging durations, crack dimensions with a maximum length exceeding 30 μm in the WC sample generally exceed those in the FC sample and AC sample. The variation is attributed to the difference in microstructures of the samples, predominantly lath bainite (LB) in water-cooled samples, granular bainite (GB) in air-cooled samples, and ferrite/pearlite (F/P) in FC samples. The research results demonstrate that the sensitivity of lath bainite (LB) to HIC is significantly higher than that of pearlite, ferrite, and granular bainite (GB). The presence of a large amount of martensite/austenite (M/A) constituents within bainite results in a multitude of hydrogen trap sites. HIC cracks in bainite generally propagate along the profiles of M/A constituents, showing both intergranular and transgranular cracking modes. [ABSTRACT FROM AUTHOR]

Long-distance gas pipelines in service inevitably are exposed to harsh conditions such as extreme temperature. It is also recognized that corrosion is one of most influential factors on the structural reliability and safety of pipelines, even coated pipelines. Therefore, there is an important need to investigate the temperature effect on the failure behaviors of gas pipelines with corrosion. In this study, a thermomechanically nonlinear finite-element model of a corroded gas pipeline with a polyethylene protective layer was established, in which a large diameter is considered for the long-distance gas pipeline. Thermal stresses obtained from cases with and without the protective layer were compared. Based on the stress-based failure criterion, the failure pressure values of corroded pipeline at different temperatures were obtained, and the deformation and strain of the corroded pipeline were evaluated. The random forest algorithm was adopted to analyze the parametric sensitivity of failure pressure. Taking temperature into account, an estimation model for predicting the failure pressure of corroded pipelines is proposed using the nonlinear least-squares method, which could be useful for performing a preliminary assessment of the failure pressure of long-distance gas pipelines in practice. [ABSTRACT FROM AUTHOR]