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THE INFLUENCE OF INSULATION MATERIALS ON CORROSION UNDER INSULATION

Picture for THE INFLUENCE OF INSULATION MATERIALS ON CORROSION UNDER INSULATION
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The designer of industrial equipment and piping has three weapons in the fight against corrosion
under insulation (CUI). The first and primary defense against CUI is a high quality, immersion
grade coating. The second is a properly designed and installed weather barrier jacketing. The third
and, arguably, least understood element is the choice of insulation material. This paper will explore
the ways in which insulation materials influence CUI behavior, presenting results from both
laboratory and field-testing on seven industrial insulation materials and one composite system.
The materials tested were calcium silicate, expanded perlite, cellular glass, mineral wool (both
regular and water-repellent grade), and two types of flexible aerogel blanket material -Pyrogel
XT and Cryogel Z

Product Number: MPWT19-15362
Author: John Williams, Owen Evans
Publication Date: 2019
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A Prediction and Inspection Technology for Detecting the Corrosion Under Insulation

Product Number: MPWT19-15162
Author: Ayman Amer, Ali Al Shehri, Vincent Cunningham, Ihsan Taie
Publication Date: 2019
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Corrosion under insulation (CUI) is a critical challenge that affects the integrity of assets for which the oil and gas industry is not immune. Over the last few decades, both downstream and upstream industry segments have recognized the magnitude of CUI and challenges faced by the industry in its ability to handle CUI risk-based assessment, predictive detection and inspection of CUI. It is a concern that is hidden, invisible to inspectors and prompted mainly by moisture ingress between the insulation and the metallic pipe surface. The industry faces significant issues in the inspection of insulated assets, not only of pipes, but also tanks and vessels in terms of detection accuracy and precision. Currently, there is no reliable NDT detection tool that can predict the CUI spots in a safe and fast manner. In this study, a cyber physical-based approach is being presented to identify susceptible locations of CUI through a collection of infrared data overtime. The experimental results and data analysis demonstrates the feasibility of utilizing machine-learning techniques coupled with thermography to predict areas of concern. This is through a simplified clustering and classification model utilizing the Convolutional Neural Networks (CNN). This is a unique and innovative inspection technique in tackling complex challenges within the oil and gas industry, utilizing trending technologies such as big data analytics and artificial intelligence.
Picture for Understanding Insulation Chemistry Proven to Inhibit Corrosion Under Insulation (CUI)
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Understanding Insulation Chemistry Proven to Inhibit Corrosion Under Insulation (CUI)

Product Number: 51317--8876-SG
ISBN: 8876 2017 CP
Author: David Shong
Publication Date: 2017
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Since 2002, a corrosion inhibiting chemistry package has been an integral part of two specific industrial insulations. This paper explains, at a molecular level, how this package engages a two-pronged defense (physical coating and pH buffering) against CUI.
Picture for Cyclic CUI Testing of Insulation Materials
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Cyclic CUI Testing of Insulation Materials

Product Number: 51317--8877-SG
ISBN: 8877 2017 CP
Author: Soeren Rasmussen
Publication Date: 2017
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Via the testing of six generically different insulation materials, the study has tried to identify factors in an insulation material that are more influential on corrosion rates of carbon steel.

 
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