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Current coating practice requires the thickness of anti-corrosion organic coatings to be over 250 for immersion parts of ships and offshore structures and the protective performance of these coatings has been evaluated by destructive and qualitative analysis. Recently, Electrochemical Impedance Spectroscopy (EIS) method has been employed, as an alternative, to evaluate corrosion resistance of organic coatings. This method is characterized as being nondestructive, reproducible, and quantitative in evaluating aging of organic coatings.
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Advanced technology high performance tank linings are often applied by plural spray equipment and occasionally one of the components could be off ratio. Worse still, some well-intentioned field personnel might add more curing agent to speed up the cure, or alter other properties, or may not utilize the entire curing agent portion in a single leg application. This paper investigates the effects of under-cure or over-cure on the performance of two high temperature tank linings by deliberately mis-mixing the two components.
Zinc-Rich Primer (ZRP) based coating systems are widely used to protect steel infrastructure from aggressive exposure environments. These coating systems provide corrosion protection of the steel substrate by both barrier and sacrificial mechanism. Electrical continuity between the zinc pigments and steel substrate is the fundamental parameter in order to achieve galvanic protection and the use of high pigment volume concentration may not necessarily ensure effective electrical continuity. Moreover, high zinc content also degrades the bond of the coating matrix to the steel substrate. Carbon nanoparticles are being considered in the development of ZRP coating systems to overcome these limitations considering its physical, electrical and mechanical properties. In this effort, a nanoparticle enriched zinc-rich primer coating system (NPE-ZRP) was evaluated to identify the influence of nano-particles on moisture intrusion of the coating system. A traditional inorganic zinc-rich coating system (ZRP) was also evaluated to compare the overall performance of the NPE-ZRP coating system. Pre-exposure to the different levels of humidity (5%, 75% & 100% RH) was incorporated to identify the coating robustness and the influence of nano-particles to mitigate corrosion. Environmental pre-exposure to humidity didn’t appear to have a detrimental effect on the coating durability. Both coatings allow moisture intrusion inside the system and EIS can be used as an effective tool to estimate the moisture content.
Throughout the oil and gas industry, carbon steel continues to be the material of choice for most downhole production tubulars and pipelines. Given the environment of typical oilfield operations, comprehensive integrity management programs are followed to guard against the threats of internal corrosion and material degradation of such assets. Although there are various corrosion mitigation options available, the application of corrosion inhibitor chemical products is commonplace given their relative ease of use and cost effectiveness.
A test methodology is shown for field application of electrochemical impedance spectroscopy (EIS). The method utilizes low-cost, accessible materials to secure a temporary solution cell to the infrastructure’s coated surface. A laptop computer provides the power source and operating system for the mobile potentiostat during EIS data collection. This data provides a quantitative measure of the coating condition. The objective of this work is to incorporate EIS testing into standard coatings inspection to estimate remaining service life for the intact coating, which improves coatings maintenance planning for facility owners.
Electrochemical Impedance Spectroscopy (EIS) has maintained a presence in protective coatings laboratories for decades. EIS is valuable in that it captures resistive and capacitive changes to a coating film as it is exposed to the environmental conditions that produce these changes, i.e., degradations. It also assists in ranking coating systems for their anticipated corrosion protection performance, complementing qualitative, visual observations.
In most engineering and scientific applications, machine learning (ML) or artificial intelligence (AI) methods in general, are primarily oriented to design a statistical/heuristic procedure to predict the outcome of a system under new conditions. This mechanism aims at exploring non-evident correlations between inputs and outputs that are embedded in the data. However, a large body of this effort relies on black-box function approximations (e.g., neural networks) that have shown limitations to elucidate additional insights from the underlying physical process that generated the data. Thus, this type of knowledge is generated in a data-driven manner without fully explaining the physics governing the problem.
A review of galvanized steel and painted galvanized steel processes is provided, as well as the fundamentals and requirements for painted galvanized steel products. The corrosion processes found with both galvanized steel and painted galvanized steels are discussed.
Corrosion under insulation (CUI) is a costly and complex problem for industry to contend with successfully. This paper describes a suite of accelerated laboratory tests undertaken in part to evaluate some of the claims made for engineered coatings touted to possess high heat resistance to 400°C and simultaneous anticorrosion properties.