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Increasingly demanding environmental regulations for industrial maintenance coatings have put pressure on manufacturers and users of both solvent borne and waterborne coating systems. The lowering of volatile organic compound (VOC) levels to as low as 100g/L is being considered for industrial maintenance coatings in many regions of the country and has already been implemented in the South Coast Air Quality Management District region of California.
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A cornerstone of aging management programs for commercial nuclear reactors is the condition monitoring techniques used to determine insulation degradation of cables. Improved condition monitoring methods has been the focus of research especially for low voltage cables. There are many effective methods available such as elongation at break, indenter modulus, oxidation induction, etc.
Low-cycle fatigue endurance of Fiber-Reinforced Thermosetting-Resin Pipe (RTRP) spools with adhesive-bonded Taper joint, overwrapped adhesive bonded Taper joint, and Butt & Wrap joint was evaluated in accordance with Section X4.3.3 under Appendix X4 in ASTM F1173.
This presentation focuses on Abrasive Blasting as it is the most widely form of surface preparation in the Protective Coating Industry. It is a brief but comprehensive presentation of the top 5 mistakes made when Abrasive Blasting and how these can be resolved to lower the total cost of a surface preparation project.
Based on US Energy Information Administration (EIA) Annual Energy Outlook (AOE) predictions, by 2050, the US nuclear capacity for electricity generation may decrease to ~ 80% of 2021 levels, Moreover, by 2050, nearly 50% of the existing US LWR fleet will be within 10 years of 80 years of operation suggesting that without a Life Beyond 80 (LBE) plan and limited new builds and advanced reactors, the US could lose up to 50% of its nuclear capacity resulting in a ~30-gigawatt (GW) capacity shortage by 2060. These numbers could change dramatically depending upon oil and gas supplies, and the growth of renewables.
Machine learning is a method that allows interpretations of new data using an established database of older data by referring to already-known results (known as “labels”) and extrapolating between them to estimate the label that would be assigned to a different experiment. This can be a powerful tool for corrosion prediction because it makes it possible to estimate a range of corrosion rates for a certain family of materials in a specific range of environments without actually performing experiments. In this paper the machine learning concept was applied to the erosion-corrosion of steels in white liquor a strongly alkaline industrial chemical used for pulping wood chips. Previously obtained corrosion data in white liquor which included different steel compositions particle concentrations and sizes temperatures and fluid properties such as viscosity were compiled and assigned labels based on previous assessments in the industry as passive acceptable marginal or unsuitable according to observed corrosion rate. Models using thirty selected variables were built based on this data using diverse machine learning methods including support vector machines (SVM) decision trees k-nearest neighbor methods (KNN). discriminant analysis etc. Feature selection was attempted for each model. The best accuracies for each method were compiled and assessed regarding their promise for predictive purposes in erosion-corrosion.
Maintaining aged infrastructure can be challenging, especially when structures were designed with difficult-to-coat features, such as riveted construction, back-to-back plates, or skip welds. According to NACE SP0178 - Design, Fabrication, and Surface Finish Practices for Tanks and Vessels to be Lined for Immersion Service, these construction methods are not recommended for immersion service.
Sports facilities are constructed in nearly every city of the country and the world. Just as these cities themselves are unique in many ways, the facilities that serve the city’s athletes must also be unique. Programs for the design of these facilities must consider natural and man-made environments. But just how do these affect design and maintenance considerations?
Residential contractors who focus on becoming a service business can bring in ongoing revenue from existing customers through regularly scheduled maintenance coats. Every contractor should have a long-range system for tracking maintenance due dates, notifying customers and even set-up maintenance contracts to gain pre-approval of future work.
This paper will explore the process of conducting asset integrity management systems and the potential use for the existing facility data to analyze integrity status and predict any breach of integrity that would cause a direct major incident. In the dawn of the 4th industrial revolution and in the age of automation and artificial intelligence, asset integrity management systems are being integrated into a more sophisticated process of verification. Programs are being used to collect necessary risk-based data from inspection, maintenance programs and operational checklists in order to rationalize the integrity status and alert proponents of possible breach of integrity. These systems are more efficient than humans in predicting possible failures based on collective data from several critical elements from a facility and calculate the probability of failure based on the current integrity status. It is possible to optimize such systems to eliminate the human error factor and optimize inspection, maintenance and operation programs to better manage asset integrity. The result would be a software that would provide an overview of the plant’s integrity status and provide early alerts of any incoming incident event which allows the facility’s management to act accordingly and direct resources for effective prevention and mitigation.
Overcoating and other maintenance painting practices of the Texas Department of Transportation are discussed.