| 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, 
											