Browse Topic: Metals
This SAE Aerospace Standard (AS) defines the requirements for a convoluted polytetrafluoroethylene (PTFE) lined, metallic reinforced, hose assembly suitable for use in aerospace fluid systems at temperatures between -65 °F and 400 °F for Class 1 assembly, -65 °F and 275 °F for Class 2 assembly, and at operating pressures per Table 1. The use of these hose assemblies in pneumatic storage systems is not recommended. In addition, installations in which the limits specified herein are exceeded, or in which the application is not covered specifically by this standard, shall be subject to the approval of the procuring activity.
This specification covers a corrosion- and heat-resistant cobalt alloy in the form of round wire 0.001 to 0.140 inch (0.025 to 3.56 mm), inclusive, in nominal diameter supplied in straight lengths or coils.
This specification covers a corrosion- and heat-resistant cobalt alloy in the form of round wire 0.001 to 0.140 inch (0.025 to 3.56 mm), inclusive, in nominal diameter supplied in straight lengths or coils (see 8.7).
This specification covers an aluminum alloy in the form of extruded bars, rods, shapes (profiles), and tubing 0.250 to 3.000 inches (6.35 to 76.20 mm), inclusive, in nominal diameter, least thickness, or nominal wall thickness (see 8.5).
This specification covers a titanium alloy in the form of sheet, strip, and plate up to 1.000 inch (25.40 mm), inclusive (see 8.6).
This specification covers an aluminum alloy in the form of extruded bars, rods, wire, shapes, profiles, and tubing.
This specification establishes testing methods and maximum permissible limits for trace elements in nickel alloy castings and powder materials. It shall apply only when required by the material specification.
This specification covers a corrosion-resistant steel in the form of bars and forgings 8 inches (203 mm) and under in nominal diameter or maximum cross-sectional dimension and forging stock of any size.
This specification covers a magnesium alloy in the form of permanent mold castings (see 8.6).
This specification covers an aluminum alloy in the form of seamless drawn tubing from 0.025 to 0.500 inch (0.64 to 12.70 mm), inclusive, in wall thickness (see 8.5).
This specification covers an aluminum alloy in the form of die forgings 4 inches (102 mm) and under in nominal thickness at time of heat treatment, hand forgings up to 6 inches (152 mm), inclusive, in as-forged thickness, rolled rings with wall thickness up to 3.5 inches (89 mm), inclusive, and stock of any size for forging or rolled rings (see 8.6).
This specification covers an aluminum alloy in the form of hand forgings up to 6 inches (152 mm), inclusive, in nominal as-forged thickness and having a cross-sectional area of not more than 156 square inches (1006 cm2) (see 8.7).
This specification covers a titanium alloy in the form of sheet and strip 0.125 inch (3.18 mm) and under in nominal thickness (see 8.6).
This specification covers an aluminum alloy in the form of plate 3.001 to 9.000 inches (76 to 229 mm), inclusive, in nominal thickness (see 8.5).
This specification covers an aluminum alloy in the form of extruded bars, rods, and shapes up to 4.000 inches (101.60 mm), inclusive, in nominal diameter or least thickness and having a nominal cross-sectional area up to 20 square inches (129 cm2) (see 8.5).
This specification covers a magnesium alloy in the form of permanent mold castings (see 8.6).
This specification covers an aluminum alloy in the form of plate 1.0 to 6 inches (25.4 to 152.4 mm), inclusive, in nominal thickness (see 8.5).
This specification covers an extra high toughness, corrosion-resistant steel in the form of bars, wire, forgings, flash-welded rings, and extrusions up to 12 inches (305 mm) in nominal diameter or least distance between parallel sides (thickness) in the solution heat-treated condition and stock of any size for forging, flash-welded rings, or extrusion.
This specification covers an aluminum alloy in the form of extruded bars, rods, wire, profiles, and tubing with a nominal diameter or least thickness (wall thickness of tubing) up to 5.000 inches (127 mm), inclusive (see 8.5).
This specification covers a titanium alloy in the form of bars up through 10.000 inches (2540 mm) in nominal diameter or least distance between parallel sides, inclusive, with bars having a maximum cross-sectional area of 79 square inches (509.67 cm2), and stock for forging of any size (see 8.7).
This specification covers an aircraft-quality, low-alloy steel in the form of mechanical tubing.
This specification covers an aircraft-quality, low-alloy steel in the form of mechanical tubing.
This specification covers an aluminum alloy in the form of extruded profiles 0.750 to 1.500 inches (19.05 to 38.10 mm) in nominal thickness with a maximum cross-sectional area of 19 square inches (123 cm2) and a maximum circle size of 11 inches (279 mm) (see 8.6).
This specification covers discontinuously reinforced aluminum alloy (DRA) metal matrix composites (MMC) made by mechanical alloying of the 2124A powder and SiC particulate, which is then consolidated by hot isostatic pressing (HIP) into shapes less than 62 square inches (0.04 m2) in cross-sectional area (see 8.12).
This specification covers one grade of commercially pure titanium in the form of bars, wire, forgings, and flash-welded rings up to 5.000 inches (127.00 mm), inclusive, in nominal diameter or least distance between parallel sides and stock for forging or flash-welded rings (see 8.6).
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
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