Extreme Learning Machine Method Based Optimization of Ta Content in CLAM Steel

摘要

Material is one of the key issues for the realization of fusion energy. Reduced Activation Ferristic/Martensitic steels (RAFMs) are considered as the primary candidate structural materials for fusion DEMO reactors and the first fusion power plants. Composition is one of the key factors determining the properties of materials. And investigation of the effect of Ta content on RAFM steel properties has very important significance.