Browse Topic: Aluminum
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 test procedure defines a laboratory procedure for generating and evaluating filiform corrosion on painted aluminum wheels and painted aluminum wheel trim. While this test was developed specifically for the testing of painted aluminum wheels and wheel trim, it may be applicable to other components. The application owner will need to assess if this test generates filiform similar to that found in the relevant usage to ensure it will provide accurate data for the application.
This specification covers an aluminum bronze alloy in the form of bars, rods, forgings, and forging stock.
This specification covers aluminum and aluminum alloy foil in the form of laminated sheet (see 8.6).
In the fall of 2023, NASA hot fire tested an aluminum-based, 3D-printed rocket engine nozzle. What made the event remarkable is that aluminum isn’t typically used for additive manufacturing because the process causes it to crack, and it isn’t used in rocket engines due to its low melting point. Yet the test was a success.
Eight arguments for these resins, compounds and composites. Weight reduction in EV battery components is an important factor in optimizing battery energy density, which in turn is critical to extending vehicle range and boosting power and performance. Although traditional metals such as steel and aluminum are widely used in EV batteries, the ongoing push for higher energy density is opening new opportunities for thermoplastic resins, compounds, and composites. The main advantage of these materials vs. metals is their inherent lighter weight - particularly in the case of lower-density polymers. Thermoplastics can be 30-50 percent lighter than metals. They also increase design freedom, which permits further weight-out through part consolidation and thin walls.
This SAE Aerospace Recommended Practice establishes the requirements and procedures for eddy current inspection of open fastener holes in aluminum aircraft structures.
This specification covers an aluminum bronze alloy in the form of sand castings (see 8.5).
Military performance requirements for adhesives have been traditionally derived to fulfill niche defense needs in harsh operational environments with little consideration for dual-use commercial potential. U.S. Army Research Laboratory, Aberdeen, MD The term “military-grade” can have a variety of meanings that are perspective dependent. In 2014, Ford Motor Company emphasized the term heavily in advertising campaigns to garner consumer acceptance for the transition from steel to aluminum in the body of their flagship F150 model. As cited by Ford, “Engineers selected these high-strength, military-grade aluminum alloys because of the metals' unique ability to withstand tough customer demands.” From this point-of-view, military-grade implies superior performance. However, the bureaucratic and logistical barriers required for certification to military-grade acceptance levels per DoD performance requirements can also be perceived as impediments to innovation and the transition of fundamental
The term “military-grade” can have a variety of meanings that are perspective dependent. In 2014, Ford Motor Company emphasized the term heavily in advertising campaigns to garner consumer acceptance for the transition from steel to aluminum in the body of their flagship F150 model. As cited by Ford, “Engineers selected these high-strength, military-grade aluminum alloys because of the metals’ unique ability to withstand tough customer demands.” From this point-of-view, military-grade implies superior performance. However, the bureaucratic and logistical barriers required for certification to military-grade acceptance levels per DoD performance requirements can also be perceived as impediments to innovation and the transition of fundamental science into tangible product. This is in-part due to the legacy age of many DoD performance standards dating to the 1950s and 1960s when the US military peaked in technology market share and was responsible for approximately two-thirds of domestic
While Daimler Truck and Paccar are pursuing LFP battery cells, Volvo Trucks employs lithium-ion batteries in which lithium nickel cobalt aluminum oxide (NCA) is used as the cathode — for now anyway. The Swedish truck maker is continuously exploring other battery technologies.
This SAE Aerospace Information Report (AIR) is intended to be used as a process verification guide for evaluating implementation of key factors in repair of metal bond parts or assemblies in a repair shop environment. This guide is to be used in conjunction with a regulatory approved and substantiated repair and is intended to promote consistency and reliability.
This specification establishes the requirements for a hard anodic coating on aluminum and aluminum alloys.
As data science technologies are being widely applied on various industries, the importance of data itself increased. A typical manufacturer company has a vast data set of products as 2D&3D drawing formats, but a common problem was that building a database from the 2D&3D drawings costs much, and it is hard to update the database after it once built. Also, it is high-cost job when the new factor researched and necessary to investigate the new factors on previously fixed or uploaded drawings. As new products are developed with time, these problems are getting more difficult. In this paper, an automated database building method using CATIA introduced and future probabilities are suggested. An aluminum wheel part was used as an example. An automated logic used CATIA V5’s VBA functions and was handled by python programming language. Product database was established by using the automated logic for extracting engineering design features, and data mining process was deployed based on the
Items per page:
50
1 – 50 of 4410