奥氏体
材料科学
马氏体
冶金
铌
贝氏体
钒
工作(物理)
无扩散变换
粒度
微观结构
热力学
物理
作者
C. Capdevila,Francisca G. Caballero,C. Garcı́a de Andrés
标识
DOI:10.1179/026708303225001902
摘要
The stabilisation of austenite, a phenomenon that frequently occurs, renders the transformation from austenite to martensite difficult. The straightforward method of analysing the effect of a specific factor on the stabilisation of austenite is through its influence on the martensite start temperature M s. The present work outlines the use of an artificial neural network to model the M s of engineering steels based on their chemical composition and austenite grain size. The results are focused on elucidating the role in the stabilisation of austenite of alloying elements in steels, including less common elements such as vanadium and niobium, as well as the austenite grain size. Moreover, a physical interpretation of the results is presented.
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