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Synthesis of materials for immobilization of well-known pH indicators, added to coatings for corrosion sensing: Layered double hydroxides, silica nanocapsules and polymeric microcapsules (chitosan). Characterized by X-ray diffraction, Fourier transform infrared spectroscopy and scanning electron microscopies.
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Evaluating the location-based risk of corrosion is critical to a number of fields of industry. Within naval aviation, knowing the risk of corrosion from environmental factors can be used to ensure that maintenance intervals are properly planned. From a basic research aspect, understanding how different sites behave allows researchers to better correlate how performance at a standard test site can be extrapolated in future research efforts. However, a survey of literature and conversations with many corrosion experts has shown variability in how environmental factors are assessed.
To reduce maintenance costs while maintaining safety, different corrosion mitigation strategies have been utilized. In addition to new structural materials and advanced protective coatings, improved maintenance planning approaches, including Condition Based Maintenance (CBM) approaches, have seen growing use over the past decade. One goal of any Condition Based Maintenance (CBM) effort is to use all available on-aircraft data as well as field and depot-based maintenance information to align resources in a timely manner to ensure aircraft safety while reducing maintenance and repair costs.
We live in a data driven world where technology is constantly evolving and making our lives easier, but even with this progression, industrial facilities are still struggling with the lack of reliable and sufficient data. LoRa has the capability to affordably expand remote sensing technologies in industrial applications, thereby improving operational efficiency, automating processes, and improving safety. With several different types of sensors available, and many more being created every year, LoRa is set to become the industry standard for the Industrial Internet of Things (IIoT).
Safe and stable operation of the process plant through its life cycle is an ultimate target of any integrity management system. Over the last decades, a number of possible ways and systems for managing plant integrity were described and implemented.1-4 A common path for all those efforts was to control and manage corrosion processes in a more-or-less systematic way by applying certain measures (monitoring techniques, material selection guidelines, operating procedures etc.) and performance indicators (remaining time-to-failure, inhibitor usage etc.). An effective corrosion and integrity management system, in theory, should be capable to “uncover” excessive corrosion incidents before serious damage occurs. Unfortunately, unexpected corrosion-related failures are still occurring in the petroleum industry.5 This situation stems predominantly from relatively poor data organization and management, leaving corrosion and key process information spread and hidden across different refinery functions and systems.
The range of factors affecting the susceptibility of equipment to corrosion under insulation (CUI)are numerous. Some of these factors might be controlled through better design, more robustinstallation procedures, and using better quality coatings. However, there are other risk factors such as operating temperature, material type, and environmental conditions that cannot be easily modified.