AMPP Store - Online Conference Paper

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A Comprehensive Empirical Evaluation of Probabilistic Corrosion Growth Rate Models

Product Number: 51323-18883-SG

Author: Gabriel Langlois-Rahme, Mahmoud Ibrahim, Miaad Safari, Yanping Li, Chike Okoloekwe

Publication Date: 2023

$20.00

Traditional Corrosion Growth Rate (CGR) models used in the integrity assessment of corroded pipelines are deterministic. A common Magnetic Flux Leakage (MFL) inline inspection (ILI) tool performance specification on general corrosion anomaly depth is +/- 10% Wall Thickeness (WT) at 80% confidence which corresponds to a standard deviation of 7.81% WT. Probabilistic Corrosion Growth Rate (PCGR) models incorporate these large measurement uncertainties and provide more realistic reliability assessments

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A Damage-Based Approach and Predictive Modeling of Corrosion in Substrate/Coating Systems Using Artificial Neural Networks

Product Number: 51324-21150-SG

Author: Victor Ponce; Walter Tarr; Allison Mahood; Heather Eich; Homero Castaneda

Publication Date: 2024

$40.00

The long-term performance of three different automotive surface coatings (physical barrier, sacrificial, and hybrid) was predicted using electrochemical impedance spectroscopy (EIS). Corrosive conditions faced by vehicles in the field, such as deicing, can be simulated using accelerated methods. The coating/metallic substrate interface experiences various degradation mechanisms during exposure to harsh conditions. In this work, real-time measurements were performed via EIS testing to characterize the degradation and corrosion mechanism of coating and substrate. After the real-time measurements, a mathematical framework based on mechanistic and machine-learning concepts was developed. Phase angle plots from EIS were utilized to monitor the state of the coating during steady-state conditions and train the Artificial Neural Network (ANN) as an arrangement of Time Series Prediction (TSP). The transport processes, activation, and interface interaction with the corrosive environments were analyzed as a corrosion mechanism and were predicted via the ANN model. The ANN has predicted the coating performance for several years, and the experimental results have been validated by employing scanning electron microscopy (SEM) imaging. Each coating condition has been validated via SEM imaging at the initial state and when the coating protection is activated.

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A Data Driven Approach to Improving Suitability of External Corrosion Risk Algorithm for Pipelines with Unique Operating Conditions – A Case Study of Hot Bitumen Pipelines

Product Number: 51323-19170-SG

Author: Cathy Lee Tetreault, Qing Lan

Publication Date: 2023

$20.00

Suncor is an integrated oil, gas exploration, and production company that operates over 1000 km (622 miles) of pipeline in Canada and approximately 386 miles (621 km) of pipeline in US. Suncor also operates refineries in Alberta, Ontario, Quebec (Canada) and in Colorado (USA). Additionally, the company owns a network of more than 1,800 Petro-CanadaTM retail and wholesale locations across Canada.

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A Data-Driven Approach to Predicting Oxidation Rate Constants For Alloys

Product Number: 51323-19412-SG

Author: Christopher D Taylor

Publication Date: 2023

$20.00

High-temperature service places severe constraints on materials selection due to a combination of factors including the formation of oxide films, spallation and volatilization, and deterioration in mechanical properties. Materials selection is principally informed by laboratory testing under simulated conditions of temperature, thermo-mechanical fatigue, and environment chemistry (such as the presence of steam, exhaust gas chemistry, or salts). Models for predicting the high temperature performance of materials a priori are an active area for development, and are currently focused on elements such as predicting oxide formation, microstructure evolution and reduced order models for creep.

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A decision support tool for best coating selection during trenchless pipe installation

Product Number: 51323-18849-SG

Author: Thierry Kerzerho, Pascal Aussant, Eric Parizot, Ahmed Fakhry, Alexandre Royer

Publication Date: 2023

$20.00

In the recent years, Horizontal Directional Drilling - HDD - became a real improvement for pipeline construction when crossing obstacles such as rivers, roads or railways. For the corrosion protection of the carbon steel pipeline, a protective coating is associated with cathodic protection. But for trenchless techniques, the coating shall withstand the stresses from the installation. Several standards are used to specify corrosion protection coatings for buried pipelines but those documents do not cover the specific conditions of an HDD.

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A Disposable Electrochemical Biofilm/MIC Test Kit to Detect MIC and to Assess Efficacy of Biocide Treatment of Biofilm

Product Number: 51324-20887-SG

Author: Lingjun Xu; Adnan Khan; Sith Kumseranee; Suchada Punpruk; Pruch Kijkla

Publication Date: 2024

$40.00

Microbial biofilms are behind microbiologically influenced corrosion (MIC). Currently, all the so-called MIC test kits on the market are actually microbe test kits. Our new disposable miniature electrochemical biofilm/MIC test kit based on 10 ml serum vials with solid-state electrodes fills the gap to provide corrosion information such as abiotic corrosion vs. MIC, and MIC by electron-harvesting biofilms vs. MIC by corrosive metabolites. It can also test antimicrobial efficacy. An electrochemical workstation is used as a base station to perform various electrochemical scans such as linear polarization resistance, electrochemical impedance spectrometry and potentiodynamic polarization scans to provide near-real time transient corrosion data after a fluid or sludge is injected into the vial. This work presented a prototype with two different solid-state electrode choices. Three different methods to distinguish MIC from abiotic corrosion, and two different methods to distinguish MIC by electron-harvesting biofilms from MIC by corrosive metabolites. Anaerobic Desulfovibrio ferrophilus IS5 (a highly corrosive sulfate reducing bacterium) biofilm, aerobic Pseudomonas aeruginosa biofilm and an anaerobic corrosive oilfield biofilm consortium were used as examples. Tetrakis hydroxymethyl phosphonium sulfate (THPS) biocide was used as an example for assessing biocide efficacy. The patent-pending technology is currently undergoing field-testing.

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A Further Look At The Impacts Of Corrosion Inhibitor On Scale Prevention

Product Number: 51322-17676-SG

Author: Qiwei Wang, Tao Chen, Hameed Al-Badairy, Sultan Alsubaie, Yasser Al-Jeshi, Mohammad Alsidan

Publication Date: 2022

$20.00

Scale and corrosion inhibitors are commonly used in many oil and gas production systems to prevent inorganic deposition and to protect asset integrity. Scale inhibitor products are based on organic compounds with phosphate or carboxylic functional groups such as amino phosphonates, phosphate esters, phosphino polymers, polycarboxylate and polysulfonates,1 as shown in Figure 1. These anionic groups have strong affinity to alkaline earth cations and can adsorb on the active growth sites of scale crystal (Figure 2), resulting in stopping or delaying the scale formation process.

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A High Performance Solvent Free Epoxy Coating Which is Applicable for High Temperature Immersion Environment

Product Number: MECC23-20000-SG

Author: Seunghyun Yang, Gokgeun Kim

Publication Date: 2023

$20.00

Crude oil and its derivate have many applications in almost all industries as O&G are the main resources that move the entire world. The oil and gas industry operate in demanding environments that pose significant challenges to equipment and infrastructure integrity. Facilities such as Gas Oil Separation Plant (GOSP) tanks, submerged areas, DGA columns, desulfurization units, and sour gas treatment facilities are subjected to high temperatures, corrosive substances, and harsh operating conditions.

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A High Performance Thermal Insulative Coating For Personnel Protection

Product Number: 51323-18941-SG

Author: Naoki Maruyama

Publication Date: 2023

$20.00

In industrial plants such as oil & gas and chemical plants, the plant piping is covered with insulative materials such as mineral wools and metal cladding for thermal insulation. The piping under insulation is subject to more severe corrosive environment than that exposed to the outdoor, due to rainwater entering through the cladding joints and condensation caused by temperature fluctuation. In addition, since the piping is covered with the insulation materials, it is impossible to identify the corrosion from the outside, increasing the risk of leakage accidents due to delays in corrosion mitigations.

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A highly-corrosive sulfate reducing bacterium as a model microbe to improve MIC investigations

Product Number: 51323-18912-SG

Author: Lingjun Xu, Sith Kumseranee, Suchada Punpruk, Pruch Kijkla, Adnan Khan, Tingyue Gu

Publication Date: 2023

$20.00

MIC is a major problem in many industrial sectors, especially in the oil and gas industry. It is widely believed that almost 20% of all corrosion costs can be attributed to MIC. The shale gas and oil industry suffers from mostly MIC rather conventional abiotic CO2/H2S corrosion. Very severe MIC with fast failures are seen in field operations with very harsh operating conditions such as high salinity and nutrient-rich water, including treated municipal wastewater that promotes microbial growth. In some situations, titanium and plastic pipes are used to cope with MIC.

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A Long-Term Inhibitor Release Technology for Corrosion and Scale Control

Product Number: 51321-16767-SG

Author: Qiongwei Li; Yulai Sun; Chengyi Gu; Hui Li; Gang Guo; Zhiping Zhou; Lihua Yang

Publication Date: 2021

$20.00

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A Machine Vision Case Study Of U-Net Networks For Superficial Corrosion And Dirt Image Segmentation On Industrial Coated Steel Structures

Product Number: 51322-17995-SG

Author: Wesley Kaizer, Otavio Correa

Publication Date: 2022

$20.00

Convolutional deep neural networks are one of the main machine learning techniques applied to computer vision and object recognition tasks. Currently, they are very popular due to their proven effectiveness in solving image classification tasks and their significant theoretical and practical importance to the advancement of the deep learning field. Examples of successful image classification networks developed are AlexNet, VGG, and GoogLeNet.^1,2,3

Online Conference Paper

Association for Materials Protection and Performance