Data-driven Multi-objective Optimization Design and Development of Ni-base Superalloy

Author of the article:DENG Yuedan1 , HU Wang2 , LIAN Lixian1 , GONG Xiufang3 , LIU Ying1 , ZHANG Yu2 , WANG Yucheng1

Author's Workplace：1. College of Materials Science and Engineering, Sichuan University, Chengdu 610065, China; 2. School of Computer Science and Engineering, University of Electronic Science and Technology, Chengdu 611731, China; 3. State Key Laboratory for Long-life High Temperature Materials, Deyang 618000, China

Key Words：Ni-base superalloy; multi-objective; machine learning; heat treatment; microstructure

Abstract：In order to develop a new nickel-based cast superalloy with excellent comprehensive performance, the candidate alloys with multi-objective characteristics such as high γ′ phase volume fraction, high γ′ phase solid solution temperature, low TCP phase content, high liquidus temperature and wide heat treatment window were designed by using machine learning and multi-objective optimization strategy. The results show that the volume fraction of γ′ phase tends to 65%, the solution temperature of γ′ phase tends to 1 210 ℃, the content of TCP phase tends to 0.01%, and the liquidus temperature is higher than 1 300 ℃ and the heat treatment interval is greater than 40 ℃ by regulating the solution temperature and time in the solution and aging heat treatment, and the multiple objectives and constraints of the expected design can be met at the same time. The prediction accuracy of the model is high. Compared with the typical brand K438 with excellent mechanical properties at high temperature, it has higher volume fraction of γ′ phase, solution temperature of γ′ phase and good application potential at high temperature.