TRIP steel

TRIP steel

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 δ ferrite dendrites and a residual phase which at high temperatures is austenite....

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Veröffentlicht in:Materials science and technology 2007-07, Vol.23 (7), p.819
Hauptverfasser: Chatterjee, S, Murugananth, M, H K D H Bhadeshia
Format: Artikel
Sprache:eng
Schlagworte:
Annealing
Chemicals
Genetic algorithms
Mathematical functions
Mechanical properties
Neural networks
Silicon
Steel
Variables
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Beschreibung
Zusammenfassung: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 δ 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 ~1 GPa and a uniform elongation of 23%. [PUBLICATION ABSTRACT]
ISSN:0267-0836
1743-2847