Browse Topic: Metals
Image-based machine learning (ML) methods are increasingly transforming the field of materials science, offering powerful tools for automatic analysis of microstructures and failure mechanisms. This paper provides an overview of the latest advancements in ML techniques applied to materials microstructure and failure analysis, with a particular focus on the automatic detection of porosity and oxide defects and microstructure features such as dendritic arms and eutectic phase in aluminum casting. By leveraging image-based data, such as metallographic and fractographic images, ML models can identify patterns that are difficult to detect through conventional methods. The integration of convolutional neural networks (CNNs) and advanced image processing algorithms not only accelerates the analysis process but also improves accuracy by reducing subjectivity in interpretation. Key studies and applications are further reviewed to highlight the benefits, challenges, and future directions of
This specification covers the requirements of uncoated aluminum alloy foil for core materials required for structural sandwich construction.
This specification covers an aluminum alloy in the form of extruded bars, rods, wire, profiles, and tubing produced with cross-sectional area of 32 square inches (206 cm2), maximum (see 8.6).
This specification covers an aluminum alloy in the form of hand forgings 11.000 inches (280 mm) and under in nominal thickness and of forging stock of any size (see 8.6).
This specification covers an aluminum alloy in the form of bars and rods 0.750 to 3.500 inches (19.05 to 88.90 mm), inclusive, in nominal diameter or least distance between parallel sides (see 8.5).
This specification covers a low-carbon steel in the form of seamless tubing up to 5.50 inches (139.7 mm), nominal OD, inclusive.
This specification covers an aluminum alloy in the form of extruded bars, rods, wire, profiles, and tubing produced with cross-sectional area of 32 square inches (206 cm2), maximum (see 8.6).
Common or obvious surface imperfections are normally visible to the naked eye before or after fabrication or processing. Illustrations and definitions of these imperfections are contained in this SAE Information Report. The identifying names are those commonly used throughout the steel industry. The imperfections identified include the major and most often encountered imperfections known to exist at this time. These imperfections are variable in appearance and severity. Extreme conditions have been selected in some instances in order to obtain suitable photographs. Photographs are courtesy of the American Iron and Steel Institute, Kaiser Aluminum, U.S. Steel, Nucor Steel, Samuel Steel, Steel Dynamics, Worthington Steel, and companies no longer in existence: LTV Steel, National Steel, and The Budd Company.
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