δ TRIP steel

被引：91

作者：

Chatterjee, S. ^{[1
]}

Murugananth, M. ^{[1
]}

Bhadeshia, H. K. D. H. ^{[1
]}

机构：

[1] Univ Cambridge, Cambridge CB2 3QZ, England

来源：

MATERIALS SCIENCE AND TECHNOLOGY | 2007年 / 23卷 / 07期

关键词：

TRIP assisted steel; martensite; bainite; delta ferrite; TRANSFORMATION-INDUCED PLASTICITY; ASSISTED MULTIPHASE STEELS; MARTENSITE-START TEMPERATURE; NEURAL-NETWORK ANALYSIS; MECHANICAL-PROPERTIES; RETAINED AUSTENITE; ALLOYING ELEMENTS; HEAT-TREATMENT; SI; MICROSTRUCTURE;

D O I：

10.1179/174328407X179746

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

A combination of neural networks and genetic algorithms has been used to design a TRIP assisted steel in which the silicon concentration is kept low. In this context, the steel has a novel microstructure consisting of delta ferrite dendrites and a residual phase which at high temperatures is austenite. This austenite can, with appropriate heat treatment, evolve into a mixture of bainitic ferrite and carbon enriched retained austenite. The steel has been manufactured and tested to reveal a tensile strength of similar to 1 GPa and a uniform elongation of 23%.

引用

页码：819 / 827

页数：9

共 53 条

[1]

[Anonymous], THESIS U CAMBRIDGE C

[2]

Bhadeshia H. K.D.H., BAINITE STEELS

[3]

BHADESHIA HKD, 2007, IN PRESS MAT SCI ENG

[4] Neural networks in materials science [J].