AMPP Store - AMPP Conference Papers

Available for download

An Overview of Significant Updates to High Voltage Holiday Detection Standards (NACE SP0188/SP0274/SP0490, ASTM D5612/G62, ISO 29601)

Product Number: 51324-21164-SG

Author: Michael Beamish; Lake Barrett

Publication Date: 2024

$40.00

High Voltage Holiday Detectors are commonly used to locate pinholes in coatings by generating a spark when an electrode passes over an area of bare substrate. Pinholes and areas of a non-continuous coating film can provide a direct path for premature failure of the coated asset. Historically a rule of thumb across the coating industry had been to utilize 100 volts per mil of coating as the recommended voltage setting for holiday detection. A paper presented at a recent AMPP conference1 provided compelling evidence, and confirmed industry suspicions, that the rule of thumb and test voltages specified by nearly every published standard were inadequate to reliably detect all holidays. In response, industry stakeholders worked to build consensus and update the relevant standards with science-based and experimentally-proven specifications that help ensure High Voltage Holiday Detectors are used appropriately, and with the correct voltage settings, to reliably detect holidays. This paper provides a review of these updates.

Available for download

Analysis and Monitoring of Welded Carbon Steel Corrosion in Aqueous Solutions Using Electrochemical Noise and Wavelet Analysis

Product Number: 51324-21243-SG

Author: Ahmed Abdulmutaali; Katerina Lepkova; Chris Aldrich

Publication Date: 2024

$40.00

The corrosion of welded carbon steel in the presence of aqueous chloride-containing solutions at 30 °C was analyzed by use of electrochemical noise (EN) and wavelet transform analysis (WTA) in three different solution systems. It is shown that features extracted from sections of the EN signals imaged by way of wavelet scalograms could be used to identify different types of corrosion, as well as for online monitoring of corrosion. Moreover, the corroded welded steel surfaces were examined using 3D profilometry to gather information about localized defects (pits). These results demonstrated that electrochemical noise associated with wavelet transform analysis, particularly wavelet scalograms, is an effective tool for monitoring localized corrosion of welded carbon steel.

Available for download

Analysis of Internal Corrosion Monitoring Data in Relation to ILI Results

Product Number: 51323-19433-SG

Author: Yevgeniy Petrov, Megan Scudder

Publication Date: 2023

$20.00

Currently pipeline operators use coupons and other monitoring data to determine if internal corrosion is active. Coupons are relatively easy to install, typically taking 1-2 days and cost around $10,000. This makes this method for collecting data attractive to operators.

Available for download

Analysis of leak repair testing requirements in ASME PCC-2 and ISO 24817

Product Number: 51323-18934-SG

Author: Pedro Bordieri, Casey Whalen, Hanna Ford

Publication Date: 2023

$20.00

Corrosion in metallic industrial equipment, pipework, and vessels, when left unchecked, can lead to the full deterioration of wall-thickness. The presence of through-wall defects may lead to loss of production and costly shutdowns, in addition to environmental and safety hazards. One solution to this issue is the installation of a repair system using composite materials, which are durable for decades, easy to install, and a cost-effective to deploy option for bringing industrial equipment back to operation, even after a leak is detected. Internationally recognized organizations, such as ASME and ISO, set the rules for the design methodology, material testing, and training of personnel for this type of repair method.

Available for download

Analysis of Pitting Susceptibility of Low Carbon Steels for the Refinement of Salt Dissolution Inhibitor Requirements

Product Number: 51323-19293-SG

Author: Joshua T. Boerstler, Bruce J. Wiersma, Keisha B. Martin, Andrea N. Bridges

Publication Date: 2023

$20.00

At Savannah River Site (SRS), High-Level Waste is stored in below-grade tanks constructed of carbon steel. This waste is composed of sludge, salt cake, and/or supernate. In part, preparation of this waste for future processing involves dissolution of the salt cake layer.

Available for download

Analytical Method to Detect and Remediate Zinc Contamination of Austenitic Stainless Steels to avoid Liquid Metal Embrittlement

Product Number: 51323-18999-SG

Author: Adrian Valenzuela, Adalberto Toledo, Robert Leggat, Lake Barrett, James Kretzler

Publication Date: 2023

$20.00

As construction of an industrial plant was nearing completion, it was realized that galvanized scaffolding was used during the erection of a large furnace. There was some concern about the possibility of zinc liquid metal embrittlement (LME) of the austenitic stainless-steel tubes. LME is the loss of ductility when a metal is in contact with liquid metal while under stress. Specifically, austenitic stainless steels are known to be susceptible to LME in the presence of liquid zinc which was implicated in the Flixborough Disaster where 28 people were killed in an industrial accident in 1974.

Available for download

Analytical Testing Equipment for Use with Industrial Coatings

Product Number: 51323-19409-SG

Author: Steve Liebhart

Publication Date: 2023

$20.00

This paper/presentation will discuss and demonstrate some uses for several analytical tools/instruments
related to troubleshooting problems associated with industrial coatings.

Available for download

Anticorrosion Performance Of Smart Release Bionanocomposite Coatings On Aluminium Alloy 6061

Product Number: 51322-18189-SG

Author: Sarah B. Ulaet, Jerin K. Pancrecious, Gincy Marina Mathew, T.P.D. Rajan

Publication Date: 2022

$20.00

Coatings for metal protection is a very broad area of research and no single formulation technique is used. Generally, coatings contain micropores, areas of low cross-link density or high pigment volume concentration that provides a diffusion path for corrosive species such as water, oxygen and chloride ions to the coating/metal interface. Therefore, incorporating corrosion inhibitors into a coating system is a basic step required for corrosion protection [1]. Direct addition of corrosion inhibitors has almost always resulted in undesirable leaching of inhibiting molecules and subsequent reactions with the coating matrix. This reduces the effect and duration required to protect the substrate in the aggressive environment. The encapsulation of corrosion inhibitors into a host material as using nanocontainers is an effective delivery system of the corrosion inhibitor in active corrosion protection application [2].

Available for download

Applicability of Martensite-Based Stainless Steels for CO2 Injection Tubing

Product Number: 51324-20636-SG

Author: Yuichi Kamo; Kenichiro Eguchi; Hiroyasu Ebina; Hiroyuki Takai; Takamasa Kawai

Publication Date: 2024

$40.00

This paper discusses the risks to the integrity of tubing material used in Carbon Capture and Storage (CCS). One risk is the formation of condensed water at the wellhead, which can lead to corrosion. FEM analysis of the waterlcontaining CO2 flux in the well indicated that the risk of corrosion due to condensed water was very low. Another risk is cooling of the tubing by cold CO2 when the temperature of CO2 is drastically decreased by the JoulelThomson effect. A cooling experiment in which cold nitrogen gas was applied to a steel pipe showed that the temperature of the steel did not decrease to the temperature of the cold gas, indicating that the cooled area was limited to the surface of the steel. The Charpy impact test demonstrated that martensitelbased stainless steels have good lowltemperature toughness. Corrosion of the steel pipe at the bottom hole, where it comes into contact with formation water, is also a risk to the material integrity. Corrosion tests of the steels in SO2 and NO2 contaminated conditions showed that not only S25CR but also modified 13CR (Mod. 13CR), 15CR, 17CR steels have good corrosion resistance in terms of the corrosion rate, resistance to localized corrosion and resistance to SCC under the SO2 and NO2 contaminated conditions.

Available for download

Applicability Study of Inhibitors to Corrosion Under Insulation

Product Number: 51323-19244-SG

Author: Takehiro Toyoda, Ayano Yasui, Hirotaka Mizukami, Yukinori Yanase, Toshiyuki Sunaba

Publication Date: 2023

$20.00

Corrosion Under Insulation (CUI) is the corrosion of piping or equipment under insulation that occurs when moisture ingresses the interface between insulation and piping or equipment, helping to form corrosion cells. CUI is one of the costliest problems shared by the oil and gas industries. One reason this problem has been a perennial challenge is that CUI is difficult to detect because it occurs under the insulation. And since it occurs regardless of the type of fluid in the pipe, every part of the plant would be included in the monitoring scope.

Available for download

Application of a Highly Corrosion-Resistant Nickel-Alloy in the Chemical Industry

Product Number: 51323-19183-SG

Author: Ajit Mishra, John Doyle, Vinay Deodeshmukh

Publication Date: 2023

$20.00

There are hundreds of commercially available alloys in the market, which is utilized by various industries, including chemicals producers. However, depending upon the corrosiveness of the process conditions, choices of materials of construction can be limited. One of a highly corrosive condition is acidic chloride chemistry (like, hydrochloric acid) in which only a handful of alloys (like, Ni-Cr-Mo alloys) can provide a reasonable service life, which though depends upon the amount of chloride, operating temperature, and impurities level.

Available for download

Application of Artificial Intelligence in Corrosion Management

Product Number: 51324-20711-SG

Author: Mohd Aswadi Ton Alias; Nurul Asni Mohamed; M Iskandar Bakeri; Izzatdin A Aziz; M Hilmi Hasan

Publication Date: 2024

$40.00

Corrosion management system encompassing the various stages of an asset life starting from design, construction, through to operation and decommissioning remains the key focus in ensuring integrity and safe operation of the asset. Corrosion study is conducted during the initial design phase, followed by multiple reviews during the operational stage as part of the overall corrosion management process. These studies aim to identify all damage mechanisms that can be present, including both non-age-related and age-related mechanisms. Currently in the oil and gas industry, corrosion rate predictions for age-related mechanisms are generated via mathematical equations or correlations as outcome from laboratory testing and analyses which may not be representative of the actual operating condition. These predictions impose limitations with regards to utilizing inputs produced from big data. Application of artificial intelligence to predict corrosion rate offers advantages where real high frequency data streams from IoT sensors are analyzed via machine learning algorithm thus providing prediction based on historical experience of specific asset. Data preprocessing is an important step in machine learning that involves transforming raw data from various parameters so that issues owing to the incompleteness, inconsistency, and/or lack of appropriate representation of trends are resolved to arrive at a data set that is in an understandable format. Feature engineering will then be performed which analyze the parameter correlation to obtain the most suitable combination and the best features and data characteristics. For corrosion rate prediction, the supervised learning algorithm is applicable such as logistic regression, naive bayes, support vector machines, artificial neural networks, and random forests. The final step of the machine learning modelling is the model validation. The predicted corrosion rates will be verified with actual thickness measurement at site. To date, we have covered 30 process units which includes different trains, 120 corrosion groups selected from a total of about 3800 corrosion groups for the whole facility. 700 customized machine learning models were developed. Success is defined by best highest accuracy (>80%) with an optimum model run time. Recent validation has shown the ability to predict an anomaly in future trend which coincides with actual increase in corrosion rate.

AMPP Conference Papers

Association for Materials Protection and Performance