Time-dependent creep-fatigue crack growth (CFCG) is an important consideration in the design and remaining life estimation of high temperature components. CFCG tests were carried out on compact type (CT) specimens of 2.25 Cr-1.0 Mo steel and its behavior, for hold times ranging from 10 seconds to 50 seconds, at 594°C (1100°F) was characterized using the average value of the Gt-parameter, (Ct)avg. The trends in the creep-crack growth (CCG) data for this material are also compared with the CFCG data. The analytically estimated values of (Ct)avg are compared with the experimental values of (Ct)avg obtained from the measured values of load-line deflection rates. It is also shown that even in the absence of accurate creep deformation constants, accurate estimates of the measured values of (Ct)avg can be obtained in CT specimens.

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Alzheimer’s disease is a chronic neurodegenerative disease that causes brain cells to degenerate, resulting in decreased physical and mental abilities and, in severe cases, permanent memory loss. It is considered as the most common and fatal form of dementia. Although mild cognitive impairment (MCI) precedes Alzheimer’s disease (AD), it does not necessarily show the obvious symptoms of AD. As a result, it becomes challenging to distinguish between mild cognitive impairment and cognitively normal. In this paper, we propose an ensemble of deep learners based on convolutional neural networks for the early diagnosis of Alzheimer’s disease. The proposed approach utilises simple averaging ensemble and weighted averaging ensemble methods. The ensemble-based transfer learning model demonstrates enhanced generalization and performance for AD diagnosis compared to traditional transfer learning methods. Extensive experiments on the OASIS-3 dataset validate the effectiveness of the proposed model, showcasing its superiority over state-of-the-art transfer learning approaches in terms of accuracy, robustness, and efficiency.

This article describes the concepts for characterizing and predicting elevated-temperature crack growth in structural materials. It discusses both creep and creep-fatigue crack growth and focuses mainly on creep crack growth tests that are carried out in accordance with ASTM E 1457. The article provides information on typical test procedures and equipment used for these tests. It concludes with information on crack growth correlations.

Economic considerations have made it desirable to extend the 30 to 40 year operating life of power plants by another 10 to 20 years. Crack growth at elevated temperatures is an important consideration in estimating the remaining life, determining operating conditions and deciding inspection criteria and intervals for power plant materials. This paper presents an overview of high-temperature crack growth phenomenon in such materials. The focus is on various techniques used for characterizing creep crack growth (CCG) and creep-fatigue crack growth (CFCG) in hightemperature materials. The collection of data, their analysis and the interpretation of results is discussed in detail, especially for CFCG laboratory testing. The discussion is primarily focussed on creep-ductile materials such as those used in power plant applications. Special considerations for elevated temperature crack growth in weldments are also presented. Finally, the application of these concepts to the life prediction of power plant components is also discussed. Keywords. Creep crack growth; power plant applications; creep-fatigue crack growth; high temperature crack growth; life of power plants.

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