Predicting aluminum-alloy mechanical properties at high temperatures

Aluminum is used for a number of applications because it is lighter than iron and easy to machine. However, Al is usually alloyed with Cu, Mg or other elements for improved strength. Developing such alloys that maintain their strength at high temperatures (over 100°C) takes a lot of time, because it requires developers’ knowledge-rich experience and performing many analysis and evaluations. Aiming to solve these problems, Showa Denko K.K. (SDK; Tokyo, Japan; www.sdk.co.jp) has been participating in a project under Japan’s Council for Science, Technology and Innovation (CSTI), Cross-ministerial Strategic Innovation Promotion Program. In this project, SDK, the National Institute for Material Science (NIMS; Tsukuba, Japan) and the University of Tokyo have collaboratively developed a computer system using neural networks — an artificial-intelligence algorithm — to accelerate the development of materials with optimal mechanical properties. The researchers focused on 2000-series Al alloys (those that contain Cu and Mg), and utilized design data of 410 records of Al alloys listed in public databases, including the Japan Aluminum Assn., and developed neural network models (NNMs) that accurately predict the strength of Al alloys…