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Picture for Pipeline Predictive Analytics Through On-Line Remote Corrosion Monitoring
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Pipeline Predictive Analytics Through On-Line Remote Corrosion Monitoring

Product Number: 51319-12899-SG
Author: Ivan Stubelj
Publication Date: 2019
$20.00

Pipelines are vast and complex networks delivering fossil fuel from remote locations to gas processing facilities refineries petrochemical manufacturers and refined products all the way to end users. Pipeline operators rely on Pipeline Integrity Management (PIM) systems to conduct safe and reliable hydrocarbon transportation operations cope with local regulations maximize transportation capacity and identify integrity threats.Internal and external corrosion are leading causes of incidents in pipelines that can lead to spills explosions and increased downtime. ASME describe the threats above as time-dependent; however they are commonly assessed with methods such as in-line inspection direct assessment and hydrostatic pressure tests whose measurement interval can range from months to years providing isolated snapshots throughout the pipeline lifetime. Moreover executing these techniques requires extensive planning and execution pipelines ready to accommodate in-line inspection tools and in some instances stop hydrocarbon transportation activities.Coping with increased demand pushes operators to boost their pipeline’s utilization rate to serve their customers and communities safely and reliably. In consequence PIM systems will require more data to constantly monitor dynamic changes along the infrastructure (either high consequence areas or not) and leverage predictive analytics. Increasing remote corrosion monitoring locations along several pipeline segments provide continuous input to feed PIM systems with on-line data that is seamlessly integrated into the operator’s control systems and data historian minimizing human intervention.This paper will explore remote corrosion monitoring technologies and how increasing real-time insights to risk maintenance and performance can increase reliability and decrease downtime through predictive analytics.

Picture for Pitfalls And Artefacts In Corrosion Experiments With Dense Phase CO2
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Pitfalls And Artefacts In Corrosion Experiments With Dense Phase CO2

Product Number: 51321-16667-SG
Author: Bjørn Helge Morland; Gaute Svenningsen
Publication Date: 2021
$20.00
Picture for Pitfalls in the Typical RBI Methodology for CUI Management Programs
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Pitfalls in the Typical RBI Methodology for CUI Management Programs

Product Number: 51324-20894-SG
Author: Ahmad Raza Khan Rana; Joel Chapman; Touqeer Sohail; Syed Umair Niaz Bukhari; Graham Brigham
Publication Date: 2024
$40.00
Modern-day risk-based inspection (RBI) platforms are designed to evaluate the safety and/or financial risk of assets using industry-recommended RBI methodologies (e.g., API 581). There are cases where the RBI methodology does not represent the true risk profile of the asset, despite implementing the best possible inspection programs and careful input of inspection data. One of the main pitfalls present is the inherent limitation in the risk calculation methodologies that makes no or little use of the inspection data. An example of such a situation is the CUI risk assessments that are subjected to uncertainties due to numerous scientific parameters that are partially addressed (or even unaddressed) in modern-day RBI approaches. This work addresses two case studies of external corrosion rates due to CUI for two pairs of test rigs made with small bore piping deployed with two different insulation designs, namely conventional design, and moisture egress design. The assemblies were tested using two different methods for CUI simulation and testing conditions. The first pair was tested per ASTM G189-07 under isothermal wet-dry conditions at 100 °C (212°F) for three days, while the second pair was submerged under water for two days followed by outdoor exposure for one year. The experimentally determined corrosion rates were compared to those calculated using API 581-compliant RBI software. The comparisons of resulting corrosion rates are complemented by an explanation of the deviations and pitfalls.
Picture for Pitting And Crevice Corrosion Resistance Of A Direct Metal Laser Sintered (DMLS) 316L Stainless Steel In Artificial Seawater
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Pitting And Crevice Corrosion Resistance Of A Direct Metal Laser Sintered (DMLS) 316L Stainless Steel In Artificial Seawater

Product Number: 51321-17006-SG
Author: Claudia Prieto; Marc Singer; David Young
Publication Date: 2021
$20.00
Picture for Pitting and Stress Corrosion Cracking Resistance of Additively Manufactured Nickel Alloy UNS N07718 in Chloride-containing Environments
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Pitting and Stress Corrosion Cracking Resistance of Additively Manufactured Nickel Alloy UNS N07718 in Chloride-containing Environments

Product Number: 51319-13359-SG
Author: Helmuth Sarmiento Klapper
Publication Date: 2019
$20.00
	Picture for Pitting Corrosion Detection by Ultrasound Monitoring
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Pitting Corrosion Detection by Ultrasound Monitoring

Product Number: 51324-20810-SG
Author: Magnus Wangensteen; Ali Fatemi; Tonni Franke Johansen; Erlend Magnus Viggen
Publication Date: 2024
$40.00
Picture for Pitting Corrosion Of A Ni-Cr-Fe Alloy In Chloride And Thiosulfate Solutions: One-Dimensional Artificial Pit Electrode Studies
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Pitting Corrosion Of A Ni-Cr-Fe Alloy In Chloride And Thiosulfate Solutions: One-Dimensional Artificial Pit Electrode Studies

Product Number: 51321-16523-SG
Author: Abraham A. Becerra Araneda/ Mariano A. Kappes/ Martín A. Rodríguez/ Ricardo M. Carranza
Publication Date: 2021
$20.00