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Interculturally, corrosion has been counted as one of the most expensive factors toward the retrogression of concrete and metallic structures resulting in huge monetary losses and unanticipated loss of life. To a large extent, corrosion-related catastrophes can be avoided by having the ability to monitor corrosion before structural integrity is jeopardized. This paper critically reviews the various accustomed electrochemical techniques utilized for corrosion monitoring in terms of their definition, timeline, experimental set-up, advantages, and shortcomings. Additionally, literature exploiting these techniques as their corrosion detection technique has been focused on here. Furthermore, a comparison between recently reported methods has been made to provide better insights into the research progress in this arena. [ABSTRACT FROM AUTHOR]

Corrosion damage presents significant challenges to the safety and reliability of connected vehicles. However, traditional non-destructive methods often fall short when applied to complex automotive structures, such as bolted lap joints. To address this limitation, this study introduces a novel corrosion monitoring approach using Lamb wave-based weighted fusion imaging methods. First, the Minimum Variance Distortionless Response (MVDR) is utilized to process Lamb wave signals collected under bolt-loosening and bolt-tightening conditions to image the bolt locations. Second, based on the identified bolt positions, the weighted Reconstruction Algorithm for Probabilistic Inspection of Damage (RAPID) is applied to the Lamb wave signals acquired before and after corrosion, enabling precise imaging of the actual positions of the corroded bolts. Experiments are conducted on three-bolt lap joints in cases of single-corrosion and two-corrosion using A0 mode Lamb waves and piezoelectric sensor networks. The results demonstrate that the proposed method effectively images multiple types of damage and achieves maximum location deviations of 7.43 mm. This approach enables precise and visual multi-damage assessment, particularly in hard-to-access regions. When integrated with V2X-enabled (Vehicle-to-Everything) systems, the method offers potential for incorporation into automotive structural health monitoring systems for remote diagnosis in complex structures, thereby enhancing monitoring efficiency and accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The high salinity, humidity, and oxygen-rich environments of coastal marine areas pose serious corrosion risks to metal structures, particularly in equipment such as ships, offshore platforms, and port facilities. With the development of artificial intelligence technologies, image recognition-based intelligent detection methods have provided effective support for corrosion monitoring in marine engineering structures. This study aims to explore the performance improvements of different modified YOLOv5 models in small-object corrosion detection tasks, focusing on five IoU-based improved loss functions and their optimization effects on the YOLOv5 model. First, the study utilizes corrosion testing data from the Zhoushan seawater station of the China National Materials Corrosion and Protection Science Data Center to construct a corrosion image dataset containing 1266 labeled images. Then, based on the improved IoU loss functions, five YOLOv5 models were constructed: YOLOv5-NWD, YOLOv5-Shape-IoU, YOLOv5-WIoU, YOLOv5-Focal-EIoU, and YOLOv5-SIoU. These models, along with the traditional YOLOv5 model, were trained using the dataset, and their performance was evaluated using metrics such as precision, recall, F1 score, and FPS. The results showed that YOLOv5-NWD performed the best across all metrics, with a 7.2% increase in precision and a 2.2% increase in F1 score. The YOLOv5-Shape-IoU model followed, with improvements of 4.5% in precision and 2.6% in F1 score. In contrast, the performance improvements of YOLOv5-Focal-EIoU, YOLOv5-SIoU, and YOLOv5-WIoU were more limited. Further analysis revealed that different IoU ratios significantly affected the performance of the YOLOv5-NWD model. Experiments showed that the 4:6 ratio yielded the highest precision, while the 6:4 ratio performed the best in terms of recall, F1 score, and confusion matrix results. In addition, this study conducted an assessment using four datasets of different sizes: 300, 600, 900, and 1266 images. The results indicate that increasing the size of the training dataset enables the model to find a better balance between precision and recall, that is, a higher F1 score, while also effectively improving the model's processing speed. Therefore, the choice of an appropriate IoU ratio should be based on specific application needs to optimize model performance. This study provides theoretical support for small-object corrosion detection tasks, advances the development of loss function design, and enhances the detection accuracy and reliability of YOLOv5 in practical applications. [ABSTRACT FROM AUTHOR]

Corrosion monitoring is crucial for ensuring the structural integrity of equipment. Acoustic emission (AE) and electrochemical noise (EN) have been proven to be highly effective for the detection of corrosion. Due to the complementary nature of these two techniques, previous studies have demonstrated that combining both signals can facilitate research on corrosion monitoring. However, current machine learning models have not yet been able to effectively integrate these two different modal types of signals. Therefore, a new deep learning framework, CorroNet, is designed to synergistically integrate AE and EN signals at the algorithmic level for the first time. The CorroNet leverages multimodal learning, enhances accuracy, and automates the monitoring process. During training, paired AE-EN data and unpaired EN data are used, with AE signals serving as anchors to help the model better align EN signals with the same corrosion stage. A new feature alignment loss function and a probability distribution consistency loss function are designed to facilitate more effective feature learning to improve classification performance. Experimental results demonstrate that CorroNet achieves superior accuracy in corrosion stage classification compared to other state-of-the-art models, with an overall accuracy of 97.01%. Importantly, CorroNet requires only EN signals during the testing phase, making it suitable for stable and continuous monitoring applications. This framework offers a promising solution for real-time corrosion detection and structural health monitoring. [ABSTRACT FROM AUTHOR]

Survey of existing repairs to buildings made of exposed concrete – Interim results of the DFG research project "How to deal with historical concrete repairs?" DFG Priority Program 2255 Cultural Heritage Construction The project aims to evaluate previous repairs to exposed concrete structures of the High Modern Age from both a heritage conservation and a structural engineering perspective, and to develop integrated strategies for their preservation. While the need for regular monitoring and condition assessment of these protected buildings is widely recognized, there is a lack of standards for monitoring strategies tailored to heritage conservation and structural engineering considerations. Accordingly, methodological approaches are presented, which were developed as interim results of the research project. The Sirius‐H recording method, developed at the Technical University of Munich allows the qualitative documentation of exposed concrete surfaces. The nature and extent of colour heterogeneity is analysed quantitatively using a spectrophotometer and paraphotographic diagrams. The CoMooD element current meter developed at the Munich University of Applied Sciences allows the measurement of carbonation‐induced reinforcement corrosion both in original concrete and in repaired areas, and thus to estimate the risk of damage. Non‐invasive investigation methods are particularly necessary for listed buildings, while the results must be documentable and reproducible in the long term in order to ensure continuous monitoring of the buildings. Based on exemplary observation results, it is shown that both methods usefully complement proven methods of condition assessment. [ABSTRACT FROM AUTHOR]

The corrosion of carbon steel reinforcements is the main cause of deterioration in reinforced concrete structures. Stainless steel can be a solution to increase the service life of structures exposed to severe chloride environments. This paper describes the results obtained in an experimental study seeking to monitor corrosion over a long-term period (10 years) without the use of accelerated tests. Concrete samples containing admixed chloride and reinforced with 5 different steel grades were exposed to high temperature and high relative humidity in a climatic chamber for 10 years. Visual inspection, corrosion potential, linear polarisation resistance and electrochemical impedance spectroscopy measurements were carried out throughout this period. Corrosion current density was calculated to monitor the evolution of corrosion. The methodology was validated on a martensitic stainless steel (grade 1.4021) with the original finding that corrosion occurs over three time steps. None of the duplex steels (grades 1.4062, 1.4362 and 1.4462) showed corrosion after 10 years, making them a very interesting solution for structures located in severe chloride environments. Mass loss corrosion laws over time were determined. Prediction of corrosion was discussed.Please check and confirm the edit made in the article title.confirmedKindly check and confirm the organization name for affiliations 1 and 2.affiliation 1: OK affiliation 2: OK [ABSTRACT FROM AUTHOR]

The economic cost of repairing corrosion-affected reinforced concrete structures (RCSs) means that reliable and accurate assessment and early detection methods must be sought after. Conventional techniques, such as visual inspections, or measuring either cover layer resistivity or the corrosion potential, are methods that require accessibility and involve personnel having to travel to take in situ measurements. Monitoring by embedded sensors is a much more efficient approach that allows early detection by remote sensing. This work presents the implementation of a new measurement protocol regarding the existing monitoring system called INESSCOM (Integrated Sensor Network for Smart Corrosion Monitoring). Along with the corrosion intensity measurement in embedded sensors, it also proposes monitoring the double layer capacity of the sensors' responses. It aims to determine, along with the rebars' corrosion rate, the triggering agent of the corrosion process. This study was carried out using three reinforced concrete scaled columns that were exposed to different environments. The results demonstrate with this new protocol that the remote INESSCOM monitoring system can establish the corrosion rate and identify the precursor agent of corrosion (carbonation or chlorides), even when the recorded corrosion rates are similar. [ABSTRACT FROM AUTHOR]

The research related to subsea inspection, and the prediction of corrosion is a challenging task, and the progress in this area is continuously generating exciting new developments that may be used in subsea inspection. Wall thickness monitoring is an important tool to control and predict corrosion, such as on platforms for the infrastructure of floating offshore wind power production. This study shows the results obtained in marine environments. For this experiment, a steel plate equipped with ultrasound transducers was placed in seawater to corrode naturally. The sensor test setup consisted of 15 ultrasound transducers and 1 temperature sensor, which were installed in the cassette. The data acquisition system was based on a standard industrial computer with software written in Python and MATLAB. The ultrasound signals were collected at regular intervals and processed to calculate the instantaneous wall thickness. The progress of corrosion was evaluated by trend plots of wall thickness versus time, and the change in shape of the ultrasonic back wall reflection waveform measured by each sensor. [ABSTRACT FROM AUTHOR]

Ultrasonic thickness measurement of mechanical structures is one of the most popular and commonly used nondestructive methods for various kinds of process control and corrosion monitoring. With ultrasonic propagation speed being temperature-dependent, the thickness measurement can be performed reliably only when the thermal profile is completely known. Most conventional techniques assume the temperature of the test structure is uniform and at room temperature across its thickness. Such assumptions may lead to large errors in the thickness measurement, especially when there are significant temperature variations across the thickness. State-of-the-art techniques use external temperature measurements or implement iterative methods to compensate for the unknown thermal profiles. However, such techniques produce unsatisfactory results when the heat distribution is complex or varies rapidly with time. In this work, we propose a two-sensors technique, using both compressive and shear excitations, with a non-iterative rapid data processing method for accurate thickness measurement under arbitrary time-variant thermal profile. The independent behavior of shear and compressive waves is used to formulate a real-time thickness estimation technique. The developed technique is experimentally validated on a steel plate with fixed acoustic sensors. Test results show that the error in thickness estimation can be reduced by up to 98% compared to conventional thickness gauging methods. [ABSTRACT FROM AUTHOR]

In the rapid development of gas fields, with the gradual increase in produced water and the extended service life of gathering and transportation pipelines, corrosion issues have become increasingly prominent. Especially the frequency of punctures and perforations is increasing year by year. In response to the serious problem of internal corrosion, the main methods for prevention and control at home and abroad are "regular pigging, pre-filming with corrosion inhibitors, and spraying". However, a reasonable system for adding corrosion inhibitors to gathering and transportation pipelines has not yet been established, and most of the related technological processes rely on engineering experience. The technical system lacks corresponding theoretical guidance and evaluation standards, resulting in technical difficulties such as poor adaptability, high dosage consumption and difficulty in controlling the quality of the protective film in the injection of corrosion inhibitors. Therefore, there is an urgent need to optimize the injection schemes of corrosion inhibitors, gradually improve the corrosion inhibitor injection technology system, develop injection schemes and technical procedures suitable for field conditions, and reduce the degree of internal corrosion and the frequency of punctures and perforations in gas field gathering and transportation pipelines. This will enhance the quality and efficiency of corrosion inhibitor application and management. In this paper, the injection process of corrosion inhibitors, the evaluation technology of corrosion inhibition efficiency, existing problems in the effectiveness of on-site injection of corrosion inhibitors and future development trends were summarized to provide references for the technology of corrosion inhibitor injection in gas field gathering pipelines.

Mapping corrosion depths along pipeline sections using guided-wave-based tomographic methods is a challenging task. Accurate defect sizing depends heavily on the precision of the forward model in guided wave tomography. This model is fitted to measured data using inversion techniques. This study evaluates the effectiveness of a recursive extrapolation scheme for tomography applications and full waveform inversion. It employs a table-driven approach, with precomputed extrapolation operators stored across a spectrum of wavenumbers. This enables fast modelling for extensive pipe sections, approaching the speed of ray tracing while accurately handling complex velocity models within the full frequency band. This ensures an accurate representation of diffraction phenomena. The study examines the assumptions underlying the extrapolation approach, namely, the negligible reflection and conversion of modes at defects. In our tomography approach, we intend to use multiple wave modes— A 0 , S 0 , and S H 1 —and helical paths. The acoustic extrapolation method is validated through numerical studies for different wave modes, solving the 3D elastodynamic wave equation. Comparison with an experimentally measured single-mode wavefield from an aluminium plate with an artificial defect reveals good agreement. [ABSTRACT FROM AUTHOR]

This paper presents the most typical corrosion mechanisms occurring in the petroleum industry. The methods of corrosion monitoring are described for particular corrosion mechanisms. The field and scope of the application of given corrosion-monitoring methods are provided in detail. The main advantages and disadvantages of particular methods are highlighted. Measurement difficulties and obstacles are identified and widely discussed based on actual results. Presented information will allow the corrosion personnel in refineries to extract more reliable data from corrosion-monitoring systems. [ABSTRACT FROM AUTHOR]

Corrosion under insulation (CUI) is a form of corrosion typically occurring on steel pipes and vessels covered with thermal insulation. CUI is a critical issue in petrochemical and refining industry leading to significant financial losses and severe environmental hazards. State‐of‐the art CUI monitoring system consisting of wireless loggers with flexible resistometric sensors is used to assess the effect of insulation material, position, and presence of a defect on the actual corrosivity toward carbon steel under alternating condensation conditions. All three considered factors together with the climatic parameters and presence of corrosion products are important for the CUI process. Most complex is the role of the insulation material as the properties inhibiting corrosion under intact insulation may be linked to a worse insulating ability. Because of the high sensitivity and immediate response of the sensors, the technique can be applied for timely CUI detection of insulated pipelines in both industrial facilities and laboratory studies. [ABSTRACT FROM AUTHOR]

In this paper，the resistance probe corrosion monitoring system and its monitoring principle were introduced.The current research progress of resistance probe corrosion monitoring technology， both domestically and internationally， was reviewed.The research status of the resistance probe corrosion monitoring system， including aspects such as the resistance probe itself， monitoring data processing， and monitoring data transmission was analyzed.The research progress in the application of resistance probe corrosion monitoring technology in three different environments， such as atmospheric， water， and soil was summarized.Finally， the prospects of resistance probe corrosion monitoring technology were presented， providing new ideas and guidance significant for the development and application of this technology.

The high salinity, humidity, and oxygen-rich environments of coastal marine areas pose serious corrosion risks to metal structures, particularly in equipment such as ships, offshore platforms, and port facilities. With the development of artificial intelligence technologies, image recognition-based intelligent detection methods have provided effective support for corrosion monitoring in marine engineering structures. This study aims to explore the performance improvements of different modified YOLOv5 models in small-object corrosion detection tasks, focusing on five IoU-based improved loss functions and their optimization effects on the YOLOv5 model. First, the study utilizes corrosion testing data from the Zhoushan seawater station of the China National Materials Corrosion and Protection Science Data Center to construct a corrosion image dataset containing 1266 labeled images. Then, based on the improved IoU loss functions, five YOLOv5 models were constructed: YOLOv5-NWD, YOLOv5-Shape-IoU, YOLOv5-WIoU, YOLOv5-Focal-EIoU, and YOLOv5-SIoU. These models, along with the traditional YOLOv5 model, were trained using the dataset, and their performance was evaluated using metrics such as precision, recall, F1 score, and FPS. The results showed that YOLOv5-NWD performed the best across all metrics, with a 7.2% increase in precision and a 2.2% increase in F1 score. The YOLOv5-Shape-IoU model followed, with improvements of 4.5% in precision and 2.6% in F1 score. In contrast, the performance improvements of YOLOv5-Focal-EIoU, YOLOv5-SIoU, and YOLOv5-WIoU were more limited. Further analysis revealed that different IoU ratios significantly affected the performance of the YOLOv5-NWD model. Experiments showed that the 4:6 ratio yielded the highest precision, while the 6:4 ratio performed the best in terms of recall, F1 score, and confusion matrix results. In addition, this study conducted an assessment using four datasets of different sizes: 300, 600, 900, and 1266 images. The results indicate that increasing the size of the training dataset enables the model to find a better balance between precision and recall, that is, a higher F1 score, while also effectively improving the model’s processing speed. Therefore, the choice of an appropriate IoU ratio should be based on specific application needs to optimize model performance. This study provides theoretical support for small-object corrosion detection tasks, advances the development of loss function design, and enhances the detection accuracy and reliability of YOLOv5 in practical applications.

Corrosion and scaling in metal pipelines are the major issues in the exploitation of geothermal sources. Geothermal fluids are complex mixtures consisting of dissolved gases and high-salinity solutions. This creates very aggressive environments primarily due to the high concentrations of carbon dioxide (CO2), hydrogen sulfide (H2S), chlorides, and other chemical species. Besides, the high temperature of the brines also increases corrosion rates, which can lead to failures related to stress and fatigue corrosion. On the other hand, reinjection of cooled brine exiting the heat exchanger favors the onset of scaling, since the chemicals dissolved in geothermal waters may tend to precipitate promoting inorganic depositions on the casing. Corrosion and scaling phenomena are difficult to detect visually or monitor continuously. Standard techniques based on pH, temperature pressure, electrical resistance measurements, chemistry composition, and physical properties are habitually applied as indirect methods for corrosion rate control. These methods, however, lack enough robustness for accurate and reliable measuring of the corrosion behavior of materials. To address this issue, a novel system has been proposed for the continuous monitoring of corrosion degradation caused by the effect of the geothermal brines. The present work aims to design, develop, and validate a dedicated electrochemical-based test system for online and onsite monitoring of the corrosion rate and scaling growth occurring on different materials exposed to real operating conditions. This system uses non-standard methods based on electrochemical impedance spectroscopy (EIS) to obtain quantitative data related to the material quality. It can be used to track the condition of the pipeline, reducing the operation and maintenance (O&M) costs and shutdown times. By providing early corrosion rate data, this system allows the prediction of failures in critical units of the plant. [ABSTRACT FROM AUTHOR]

Corrosion monitoring of reinforced or prestressed concrete structures has become increasingly important in recent years. Areas of application include components that are no longer accessible after completion or where potential field measurements cannot be carried out due to existing coatings. Corrosion monitoring can also be used to monitor the progress of corrosion in corroding systems, e.g. to prove the success of repair measures according to repair principle 8 in accordance with EN 1504‐9 or repair method 8.3 in accordance with the DIBt repair guideline. It also could be used to prove the functionality of cathodic corrosion protection systems in accordance with ISO 12696. Despite the increasing importance of corrosion monitoring, no guidelines or recommendations existed until 2018. This gap was closed by the English version of specification B12, "Corrosion Monitoring of Reinforced and Prestressed Concrete Structures," of the German Society for Non‐Destructive Testing, which was published in 2021. This article introduces specification B12 by explaining the basic measurement principles and illustrating the potential of corrosion monitoring in new and existing buildings. [ABSTRACT FROM AUTHOR]

Corrosion detection (CD) has become a high priority in chemical industries, defense and transportation sectors to extend the life of existing or new systems while ensuring the safety of the existing components and reducing downtime to minimise economic losses. Here, this article is aimed to review and discuss non-destructive techniques used widely in the industry to detect, monitor and repair corrosion problems early on. The comprehensive review provides a detailed discussion, a functional mechanism, advantages and disadvantages of crucial non-destructive CD techniques widely used in the industry, helping the reader choose the type of corrosion monitoring methods effectively. An extensive literature review of visual and optical testing techniques, acoustic emissions, eddy current, guided wave and equipment, infrared thermography, radiographic, microwave and millimeter wave, and terahertz imaging is discussed. The underlying mechanism, its merits and limitations, along with the usage scenario, is explained that can be related across different areas making it interdisciplinary research for corrosion monitoring techniques. [ABSTRACT FROM AUTHOR]

The water of Persian Gulf, which is currently used as the water in the cooling tower for Bandar Abbas power plant has high alkalinity, conductivity and salinity. The examination of microbial tests for the cooling tower indicates the high concentrations of all kinds of microbial species which is related to the high level of fluoride, sulfate ions and sediments. The TBC shows 104 cfu/ml which is considered a high value. On the other hand, the presence of magnesium and calcium ions in carbonate form is a reason for the huge amount of hardness. The high level of ions concentration especially chloride and magnesium in the cooling water increase the growth of microbial parameters. Furthermore, the reason of such a huge growth of sulfate-reducing bacteria (SRB) is the high concentration of sulfate. Therefore, the solution of reducing the general concentration of ions using methods such as reverse osmosis and ion exchange resins is suggested as the first priority to prevent microbial corrosion. Additionally, chlorination methods are proposed as the second priority due to economic efficiency and high-performance capability. Finally, ozonation method is presented as the third priority due to the higher cost compared to chlorination, high power and the absence of side products. Also, the high concentration of sulfate leads to the activity of SRB bacteria and causes various types of corrosion, and therefore, the use of methods for reducing the concentration and selective removal of sulfate as an effective and priority solution should be considered. [ABSTRACT FROM AUTHOR]

The corrosion of reinforced concrete (RC) is one of the most serious durability problems in civil engineering structures, and the corrosion detection of internal reinforcements is an important basis for structural durability assessment. In this paper, the appropriate frequency required to cause excitation signals in the specimen is first analyzed by means of frequency dispersion curves. Subsequently, the effectiveness of five damage indexes (DIs) is discussed using random corrosion in finite elements. Finally, guided ultrasonic wave (GUW) tests are conducted on reinforcement and RC specimens at different corrosion degrees, and the test results are verified using a theoretical corrosion model. The results show that the larger the covered thickness is at the same frequency, the higher the modal order of the GUW in the frequency dispersion curve is, and the smaller the group velocity is. The SAD is the most sensitive to the corrosion state of the reinforcement compared with the other DIs, and it shows a linear increasing trend with the increase in the corrosion degree of the reinforcement. The SAD values of the RC specimens showed a three-stage change with the increase in the corrosion time, and the time until the appearance of corrosion cracks was increased with the increase in the covered thickness. It can be seen that increasing the covered thickness is an effective method to delay the time until the appearance of corrosion cracks in RC specimens. [ABSTRACT FROM AUTHOR]

In order to better understand the corrosion risk of single pole operation of high-voltage direct current (HVDC) grounding electrodes on pipelines, a comprehensive review of corrosion monitoring technologies for buried pipelines over recent decades was conducted in this paper; the principles of various corrosion monitoring techniques were introduced, and the application status of different corrosion monitoring technologies in the context of HVDC interference with buried pipelines was summarized; the advantages and disadvantages of four rapid corrosion measurement methods, namely the field burial method, intelligent pile monitoring method, electrochemical reduction (ER) corrosion rate probe method and laboratory simulation experiments, in evaluating the corrosion rate of buried pipelines under HVDC interference were mainly analyzed. Based on this analysis, recommendations for the application of various corrosion monitoring techniques in the field of HVDC interference with buried pipelines were proposed. Additionally, new directions in monitoring technology for corrosion rate of buried pipelines under HVDC interference were explored, providing references for relevant researchers and engineers.

There is a great importance in investigating and measuring microbial corrosion in the cooling tower of thermal power plants, especially in the case of open cycles. Moreover, this issue becomes more important in the situation where the source of water supply for cooling tower is river or sea water. In this research, the cooling tower water for Ramin Power Plant, which is supplied from the Karun River, is examined as a point of of microbial growth. For this purpose, microbial tests including TBC (general test) and specific bacteria tests such as APB, FP, IRB, NRB, Aero, SRB and TRB, physicochemical tests (conductivity, salinity, pH, turbidity) and the amount anions and cations, are carried out in the water sample of the cooling tower. In the TBC test, the approximate number of bacterial colonies is 107 cfu/ml, which is in a very heavy range. The results of APB and IRB test indicate the value is much higher than the permissible limit and the presence of Aero bacteria. On the other hand, in the analysis of anion and cation, sulfate and chlorine species have a very high concentration of more than 1000 ppm. Therefore, to deal with microbial factors, and as a solution in the first priority, the method of chlorination with water shock is recommended. The second priority includes the general method based on oxidizers such as ozonation and bromination. Selective removal of sulfate and nitrate ions is suggested as the third priority solution due to the high concentration of these ions and the intense activities of SRB and NRB bacteria.

The water of Persian Gulf, which is currently used as the water in the cooling tower for Bandar Abbas power plant has high alkalinity, conductivity and salinity. The examination of microbial tests for the cooling tower indicates the high concentrations of all kinds of microbial species which is related to the high level of fluoride, sulfate ions and sediments. The TBC shows 104 cfu/ml which is considered a high value. On the other hand, the presence of magnesium and calcium ions in carbonate form is a reason for the huge amount of hardness. The high level of ions concentration especially chloride and magnesium in the cooling water increase the growth of microbial parameters. Furthermore, the reason of such a huge growth of sulfate-reducing bacteria (SRB) is the high concentration of sulfate. Therefore, the solution of reducing the general concentration of ions using methods such as reverse osmosis and ion exchange resins is suggested as the first priority to prevent microbial corrosion. Additionally, chlorination methods are proposed as the second priority due to economic efficiency and high-performance capability. Finally, ozonation method is presented as the third priority due to the higher cost compared to chlorination, high power and the absence of side products. Also, the high concentration of sulfate leads to the activity of SRB bacteria and causes various types of corrosion, and therefore, the use of methods for reducing the concentration and selective removal of sulfate as an effective and priority solution should be considered. [ABSTRACT FROM AUTHOR]

Copyright of Corrosion & Protection in Petrochemical Industry is the property of Corrosion & Protection in Petrochemical Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since the electrochemically integrated multi-electrode array, often referred to as the wire beam electrode, was initially developed for corrosion studies in 1990s, remarkable progresses have been made in its applications for probing and monitoring various forms of localised corrosion that are difficult-to-measure by conventional methods. This paper provides a brief overview of diverse and innovative applications of variously designed and constructed electrode array probes for measuring localised corrosion under complex environmental conditions with particular focus on the discussion of challenges and obstacles that prevent wider applications of electrode arrays. Discussion on future perspectives have included suggestions on the innovative design and fabrication of multi-scale, three-dimensional, complex shaped and patterned electrode arrays for simulating microstructural features of heterogeneous alloys and thoughts on the future integration of corrosion monitoring data and data analytics, machine learning and artificial intelligence for future prediction, modelling and prevention of corrosion in industrial applications. [ABSTRACT FROM AUTHOR]

The evaluation of the corrosion wear rate was carried out using the Norsok Standart M-506 method for oilfield production tubing in Belarus. The method is based on a model that takes into account the speed of the gas-liquid flow, its pH, the volumetric flow rate of water, oil, gas, pressure, temperature, immersion depth, pH, density and viscosity of these media, and diameter and wall thickness of tubing. A feature of the model is the consideration of the friction of the gas-liquid flow on the walls of the tubing and the resulting shear stresses near them, which allows taking into account the corrosion-mechanical component of the metal degradation process of the tubing. The characteristics of well media and operating conditions of equipment in fields are given. Empirical coefficients of the considered model for typical conditions of Belarusian oil fields have been determined and a predictive calculation of the corrosion rate of 32Mn1A tube steel strength group N80 (Q) of the API Specification 5CT has been carried out. Data on actual values of corrosion wear of tubing from more than 100 production wells have been collected. The results indicate a high convergence of calculated and actual data. The adapted Norsok Standart M-506 method of predicting corrosion wear is recommended for use at oil fields in Belarus. It is shown how the proposed approach can be extended to other oil-bearing regions. [ABSTRACT FROM AUTHOR]

Reinforced Concrete Structures (RCS) are a fundamental part of a country's civil infrastructure. However, RCSs are often affected by rebar corrosion, which poses a major problem because it reduces their service life. The traditionally used inspection and management methods applied to RCSs are poorly operative. Structural Health Monitoring and Management (SHMM) by means of embedded sensors to analyse corrosion in RCSs is an emerging alternative, but one that still involves different challenges. Examples of SHMM include INESSCOM (Integrated Sensor Network for Smart Corrosion Monitoring), a tool that has already been implemented in different real-life cases. Nevertheless, work continues to upgrade it. To do so, the authors of this work consider implementing a new measurement procedure to identify the triggering agent of the corrosion process by analysing the double-layer capacitance of the sensors' responses. This study was carried out on reinforced concrete specimens exposed for 18 months to different atmospheres. The results demonstrate the proposed measurement protocol and the multivariate analysis can differentiate the factor that triggers corrosion (chlorides or carbonation), even when the corrosion kinetics are similar. Data were validated by principal component analysis (PCA) and by the visual inspection of samples and rebars at the end of the study. [ABSTRACT FROM AUTHOR]

The assessment of infrastructure conditions is at present a topic of great interest and importance, as well as great challenge. This paper presents a case study of the Samuel De Champlain Bridge (Montreal, QB, Canada), an outstanding stay cable bridge equipped with a comprehensive monitoring system (SHM). Among other SHM features, particular attention was paid to implementation of a strategic corrosion monitoring system. This paper intends to describe the concept design, implementation and data interpretation. Here corrosion sensors have been embedded during construction stage to monitor long term evolution of key electro‐chemical parameters for controlling deterioration of materials. Furthermore, these sensors measure stray current interference generated from the rail system that can cause corrosion. In both cases, abnormal values would warn the owner of the associated increased risk of corrosion. This gives them the possibility to take corrective measures to protect the structure before corrosion becomes a serious threat. [ABSTRACT FROM AUTHOR]

Corrosion of steel in concrete is a complex process with many factors influencing its kinetics. Especially under on‐site condition, the prediction of corrosion rates is a challenge since many influencing factors such as the temperature change constantly. The whole corrosion process is the concert of three sub‐processes: (i) the anodic reaction rate, (ii) the cathodic reaction rate and (iii) the electrolytic conductivity of the concrete. Each of the processes show temperature dependency and existing corrosion monitoring systems record either data to evaluate part of the processes or the resulting corrosion rate. For service life estimates, prediction of corrosion rates is necessary. Consequently, the knowledge on the temperature effect on the corrosion rate is crucial, especially in view of rising temperatures due to climate change. This paper presents an overview on the existing knowledge on the temperature dependency on the corrosion rates; highlights the analysis of temperature data and provides guidance for service life prediction. [ABSTRACT FROM AUTHOR]

Copyright of Corrosion & Protection in Petrochemical Industry is the property of Corrosion & Protection in Petrochemical Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Introduction: The water of cooling tower for Shahid Moftah power plant is supplied from treated wastewater. Therefore, chemical control of water in order to control corrosion in this cycle is very complicated. Methods: The results of the TBC (total bacteria count) test of cooling tower indicate the approximate number of bacterial colonies equal to 103 cfu/ml, which is in the light range. According to the microbial tests, the amount of TRB, IRB and APB bacteria is very high and has values ​​of 1200, 500-2300 and 105 cfu/ml, respectively. Using treated wastewater as a feed of cooling tower due to the presence of high concentration of calcium ions leads to intensification of sedimentation and increase the growth of microbial organism. Moreover, the presence of high nitrate is predictable due to the origin of water supply, which causes the increase of nitrate and nitrite reducing bacteria (NRB). On the other hand, the presence of high phosphate and sulfate in the sample increase sedimentation and intensify microbial growth, especially sulfate-reducing bacteria (SRB) in the sample. Findings: As a result, high concentrations of TRB, IRB, and APB bacteria is required to be selectively removed in the first priority. In the second priority, nitrate and sulfate ions, which are food for NRB and SRB bacteria, need to be removed by selective removal of nitrate ions using ion exchange resins and sulfate with biological regeneration method. Due to the high level of microbial agents TRB, IRB and APB as well as the high concentration of microbial agents feed, as the third priority, methods based on non-oxidizing biocides needs to be applied in this power plant.

Bacterial biocementation has been shown to have the unique capability of healing cracks in concrete. However, there is a concern that the materials used in biocement may cause corrosion. This paper reports the performance of bacterially healed reinforced concrete when exposed to chloride-induced reinforcement corrosion. Cracks in reinforced concrete specimens were healed using two different calcium sources. After healing, the samples were subjected to 3.5% sodium chloride exposure to salt water for 120 days. The state of corrosion was assessed through standard electrochemical techniques such as half-cell and linear polarization methods as well as ultrasonic-guided waves. After the exposure period, the bars were extracted from concrete, and mass loss and tensile tests were conducted. It was found that electrochemical measurements indicated corrosion activity in the cracked specimens, but the uncracked specimen did not indicate corrosion during the entire exposure period. The presence of electrolytes in the healing fluid seems to have influenced the electrochemical measurements and gave a misleading indication of corrosion. The ultrasonic-guided waves that assess both effects of corrosion, loss of metal and bar-concrete interfacial debonding, were found to realistically assess the state of corrosion in all the samples. The rate of corrosion had slowed down significantly as a result of healing. [ABSTRACT FROM AUTHOR]

Corrosion under disbonded coatings (CUDC) remains a major unsolved issue and a prime risk to underground steel structures such as buried gas pipelines. CUDC could not be effectively mitigated by conventional cathodic protection (CP) or be detected through usual inspection and survey technologies due to CP shielding. This article provides a brief review of recent progresses made through laboratory and field probing of CUDC and its influence factors. Discussions on CUDC processes and mechanisms are made based on results from an extensive laboratory and field-testing program using electrode array-based corrosion probes. It is shown that CUDC is affected not only by well-known factors such as the CP level, but also by coating disbondment geometry and soil conditions especially the seasonal dry-wet changes in soil saturation status. These findings have led to improved understanding of CUDC, and could lead to the development of better CUDC mitigation and control methods. [ABSTRACT FROM AUTHOR]

Corrosion induced thickness loss in metallic structures is a common and crucial problem in multiple industries. Therefore, it is important to accurately monitor the corrosion amount of the structure. Traditional corrosion monitoring methods are mainly based on electrochemical methods, and most of them are unable to quantify the corrosion amount. In our previous work, a new type of corrosion sensing mechanism based on the electromechanical impedance instrumented circular piezoelectric-metal transducer was proposed, in which the peak frequencies in the conductance signatures decrease linearly with the increase of the corrosion induced thickness loss. However, only the uniform corrosion with even metal thickness decrease was considered in the previous study. In this paper, the capability of the proposed sensing mechanism for the quantification and prediction of pitting corrosion was investigated using one-dimensional convolutional neural networks (1D CNN). Finite element modeling of the pitting corrosion was performed and the probability distribution of the corrosion pits was considered. In the experimental setup, corrosion pits were generated on the corrosion sensor using mechanical drilling. The 1D CNN was adopted to explore the regression relationship between the EMI signatures of the sensor and the mass loss induced by pitting corrosion. The results show that the proposed method has achieved high accuracy in the quantitative prediction of pitting corrosion. This paper lays the technical foundation for real-time and quantitative monitoring of pitting corrosion for metallic structures. [ABSTRACT FROM AUTHOR]

Steel corrosion in concrete infrastructures is of worldwide interest. This paper reports the monitoring of concrete prestressed bridge infrastructures by autonomous sensors based on the RFID technology. Embedded autonomous sensors in concrete were produced for this purpose and tested in a laboratory environment. Subsequent tests in real environments are in progress.

Corrosion and scaling in metal pipelines are the major issues in the exploitation of geothermal sources. Geothermal fluids are complex mixtures consisting of dissolved gases and high-salinity solutions. This creates very aggressive environments primarily due to the high concentrations of carbon dioxide (CO2), hydrogen sulfide (H2S), chlorides, and other chemical species. Besides, the high temperature of the brines also increases corrosion rates, which can lead to failures related to stress and fatigue corrosion. On the other hand, reinjection of cooled brine exiting the heat exchanger favors the onset of scaling, since the chemicals dissolved in geothermal waters may tend to precipitate promoting inorganic depositions on the casing. Corrosion and scaling phenomena are difficult to detect visually or monitor continuously. Standard techniques based on pH, temperature pressure, electrical resistance measurements, chemistry composition, and physical properties are habitually applied as indirect methods for corrosion rate control. These methods, however, lack enough robustness for accurate and reliable measuring of the corrosion behavior of materials. To address this issue, a novel system has been proposed for the continuous monitoring of corrosion degradation caused by the effect of the geothermal brines. The present work aims to design, develop, and validate a dedicated electrochemical-based test system for online and onsite monitoring of the corrosion rate and scaling growth occurring on different materials exposed to real operating conditions. This system uses non-standard methods based on electrochemical impedance spectroscopy (EIS) to obtain quantitative data related to the material quality. It can be used to track the condition of the pipeline, reducing the operation and maintenance (O&M) costs and shutdown times. By providing early corrosion rate data, this system allows the prediction of failures in critical units of the plant.

Based on high-stress characteristics of prestressed anchor cables, this paper develops an axial-distributed testing method to test corrosion damage of prestressed anchor cables. The positioning accuracy and corrosion range of an axial-distributed optical fiber sensor is studied, and its mathematical model between corrosion mass loss and axial fiber strain is established. The experimental results show that the fiber strain from an axial-distributed sensor enables one to reflect the corrosion rate along a prestressed anchor. Moreover, it has a greater sensitivity when an anchored cable has a higher stress. The mathematical model between corrosion mass loss and axial fiber strain is determined to be ε = 4723.64 ρ + 2592.95 . The corrosion location along the anchor cable is characterized by axial fiber strain. Therefore, this work provides an insight for cable corrosion. [ABSTRACT FROM AUTHOR]

Copyright of Corrosion & Protection in Petrochemical Industry is the property of Corrosion & Protection in Petrochemical Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Electromagnetic techniques are widely employed for corrosion detection, and their performance for inspection of corrosion is well established. However, limited work is carried out on the development and reliability of smart corrosion monitoring devices for tracking internal or buried thickness loss due to corrosion remotely. A novel smart magnetic corrosion transducer is developed for long-term monitoring of thickness loss due to corrosion at critical locations. The reliability of the transducer is enhanced by using a dissimilar active redundancy approach. The improved corrosion monitor has been tested in the ambient environment for seven months to evaluate the stability against environmental factors and degradation. The monitor is found to show great sensitivity to detect defects due to corrosion. Detection of anomalous patterns in the time series data received from the monitors is accomplished by using Pearson's correlation coefficient. The critical component of the monitor is identified at the end of the test. Research findings reveal that, compared to the existing corrosion monitoring techniques in the industry, the detection and isolation of faulty sensor features introduced in this study can contribute to reliable monitoring of thickness loss due to corrosion in ferromagnetic structures over an extended period of time. [ABSTRACT FROM AUTHOR]