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Due to increase in global energy demand lot of LNG terminals are constructed worldwide. One such terminal is being constructed in Kuwait which has the worlds largest capacity LNG storage tanks. Effective inspection of storage tank is a challenge and require to increase operational reliability but also reduce maintenance costs. Non-Destructive testing like radiography/X-ray and ultrasonic testing are the common monitoring methods commonly used. This paper describes the application and effective use of such inspection techniques to enhance the reliability of inspection of storage tanks.Keywords : Storage tanks Radiography Ultrasonic Inspection Reliability.
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A corrosion investigation performed in 2018 on an NPS 6, approximately 4 km long, polyethylene coated pipeline determined that the accelerated corrosion anomalies detected during in-line inspections (ILI) were due to AC corrosion. The AC and DC current densities on the AC coupons adjacent to these anomalies were above the limits recommended in NACE SP21424. It was also determined that the line was cathodically over-protected, and that most of the AC voltage measured on the line was due to 120 Hz AC ripple from a foreign rectifier.
Everyone wants a quality project; the word quality means different things to different people. Owners have unique perspectives on quality and risk tolerance which often differs across industries. The owner of a trash recycling center looking to paint the walls of his loading dock has a different perspective than the owner of a nuclear power plant, looking at the coating systems applied on the interior of his primary containment walls.
In-service welding is applied for repairs or modifications for pipelines or pipework/equipment that lead to significant economic advantages by avoiding the costs of disrupting the pipeline’s operation decommissioning, draining of fluid inside piping, purging and it maintaining a continuous supply of products to customers. Moreover, in-service welding on pipelines or piping is uncommon practice due to the high risk caused by excessive heat input during weld or accelerated cooling rates. Referring to API 1104, there are two primary concerns with welding onto in-service pipelines. The first concern is to avoid “burning through,” where the welding arc causes the pipe wall to be breached. The second concern is for hydrogen cracking, since welds made in-service cool at an accelerated rate as the result of the flowing contents’ ability to remove heat from the pipe wall. This paper explores the development of an online welding procedure to weld stainless steel 304L, making branch connections to meet business requirements without disrupting the operation.
The use of passive fire protection (PFP) materials plays an integral role in mitigating fire risk in commercial buildings. Traditional application of these materials has been on-site following the erection of structural steel. Their mechanical durability, exposure to weather and in-flexibility have been a major concern for construction managers and architects.
The intention of the study is to explore potential field maintenance products with service temperature ranges of 0 to 65°C for patch application, including patch repairing and to provide corrosion protection for irregularly shaped components, such as fittings and electrical connection to pipe (e.g., cadweld). Viscoelastic materials were selected as potential candidates due to their inherent features of cold-flow capability, low water permeability, easy application (by hand and directly applied to surface), and compatibility with a variety of existing pipeline coatings.
In this study we have developed a computational end-to-end framework to investigate properties of organic corrosion inhibitors responsible for inhibition of mild steel in HCl solution. Several studies in the past have reported Quantitative Structure-Activity Relationships (QSAR) based models for predicting corrosion inhibition performance for steels. However one of the major limitations in these studies is that the authors have restricted themselves to use of only a single class of molecules. Using advanced machine learning algorithms such as support vector machines (SVM) random forest (RF) etc. we have developed a robust computational predictive model of corrosion inhibitors which is not limited to a particular class of molecules. Our model is based on quantum chemical and molecular structural parameters. Our data visualization frameworkprovides users much deeper fundamental understanding of the effect of each independent variable on corrosion inhibition. The study has identified features that have higher and consistent impact on experimental inhibition efficiency. Using these parameters we have also designed novel molecules which are having higher inhibition efficiency as predicted by our model. Our model will also help in discovering and screening of novel corrosion inhibitors which can replace existing toxic inhibitors.