|About this Abstract
||2016 TMS Annual Meeting & Exhibition
||Computational Materials Discovery and Optimization: From 2D to Bulk Materials
||A Fast Algorithm for the Discovery of Optimal Nickel-based Superalloys
||Edern Menou, Gérard Ramstein, Emmanuel Bertrand, Franck Tancret
|On-Site Speaker (Planned)
For decades, the development of high-temperatures alloys has been driven by the need for higher efficiencies in gas and steam turbines. Current operating temperatures of such systems forbid the use of steels, making superalloys a key material for both the aerospace and energy industries. Yet, despite its maturity, superalloys development remains laborious. On the one hand, design requirements become more severe, notably in terms of creep endurance and corrosion resistance. On the other hand, the palette of alloying elements as well as intricate processing and service conditions induce complex metallurgical interactions.
To overcome these difficulties, exploration of the broad compositional spectrum is outsourced to a genetic algorithm which assesses alloys capability using models for thermomechanical properties and computational thermodynamics for microstructural stability. Metallurgical criteria are integrated within the multi-objective search, providing a straightforward and efficient way of screening a large number of candidates and discovering innovative, optimised superalloys.
||Planned: A print-only volume