Prediction of austenite decomposition during cooling of low and medium-carbon low-alloy steels

被引：0

作者：

Anelli, E ^{[1
]}

Cesile, MC ^{[1
]}

Di Nunzio, PE ^{[1
]}

机构：

[1] Ctr Sviluppo Mat SpA, Rome, Italy

来源：

MODELING, CONTROL AND OPTIMIZATION IN FERROUS AND NONFERROUS INDUSTRY | 2003年

关键词：

austenite decomposition; low and medium-carbon steels; artificial neural networks;

D O I：

暂无

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

Based on experimental continuous cooling transformation (CCT) diagrams, an artificial neural network has been trained to predict the amount of microstructural constituents and hardness resulting from austenitizing and controlled cooling at rates from 150 to 0.05 K/s. It can be applied to quenching and normalizing processes of low-alloy steels with 0.05-0.30 C% and 0.4-2.0% Mn with possible microalloying additions. Examples of the good predictive capabilities (about 15 Vickers standard deviation for hardness and a few percent for volume fraction of phases) are reported.

引用

页码：453 / 466

页数：14

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