Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1502836 | Scripta Materialia | 2008 | 4 Pages |
Abstract
It has been broadly reported that determination of the martensite start temperature in steels, MsMs, requires a complete description of their chemical composition. Recently, several neural networks models considering both chemical composition and austenite grain size (AGS) have been developed. Such models predict a moderate dependence of MsMs with AGS. The present work examines the validity of existing neural network models, but focusing on fine AGS (below 5 μm).
Related Topics
Physical Sciences and Engineering
Materials Science
Ceramics and Composites
Authors
A. García-Junceda, C. Capdevila, F.G. Caballero, C. García de Andrés,