Characterization of hot flow behaviour and deformation stability of medium carbon microalloyed steel using artificial neural networks and dynamic material model

2014 ◽  
Vol 105 (8) ◽  
pp. 743-754 ◽  
Author(s):  
Ignacio Alcelay ◽  
Anas Al Omar ◽  
José Manuel Prado
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Microalloyed Steel ◽  
Material Model ◽  
Flow Behaviour ◽  
Medium Carbon ◽  
Dynamic Material Model ◽  
Deformation Stability ◽  
Carbon Microalloyed

Hot deformation behavior of a medium carbon microalloyed steel

2011 ◽  
Vol 528 (10-11) ◽  
pp. 3876-3882 ◽  
Author(s):  
H. Mirzadeh ◽  
J.M. Cabrera ◽  
J.M. Prado ◽  
A. Najafizadeh
Keyword(s):  
Hot Deformation ◽  
Deformation Behavior ◽  
Microalloyed Steel ◽  
Hot Deformation Behavior ◽  
Medium Carbon ◽  
Carbon Microalloyed

scholarly journals Hot Deformation Treatment of Grain-Modified Mg–Li Alloy

Materials ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 4557
Author(s):  
Mariusz Król ◽  
Przemysław Snopiński ◽  
Marek Pagáč ◽  
Jiří Hajnyš ◽  
Jana Petrů
Keyword(s):  
Hot Deformation ◽  
Cast Alloy ◽  
Material Model ◽  
Strain Rate Range ◽  
Al Alloy ◽  
Grain Refiner ◽  
Systematic Analysis ◽  
Dynamic Material Model ◽  
Instability Map

In this work, a systematic analysis of the hot deformation mechanism and a microstructure characterization of an as-cast single α-phase Mg–4.5 Li–1.5 Al alloy modified with 0.2% TiB addition, as a grain refiner, is presented. The optimized constitutive model and hot working terms of the Mg–Li alloy were also determined. The hot compression procedure of the Mg–4.5 Li–1.5 Al + 0.2 TiB alloy was performed using a DIL 805 A/D dilatometer at deformation temperatures from 250 °C to 400 °C and with strain rates of 0.01–1 s−1. The processing map adapted from a dynamic material model (DMM) of the as-cast alloy was developed through the superposition of the established instability map and power dissipation map. By considering the processing maps and microstructure characteristics, the processing window for the Mg–Li alloy were determined to be at the deformation temperature of 590 K–670 K and with a strain rate range of 0.01–0.02 s−1.

Characterization of Mexican coffee according to mineral contents by means of multilayer perceptrons artificial neural networks

2014 ◽  
Vol 34 (1) ◽  
pp. 7-11 ◽  
Author(s):  
Roberto Muñiz-Valencia ◽  
José M. Jurado ◽  
Silvia G. Ceballos-Magaña ◽  
Ángela Alcázar ◽  
Julio Hernández-Díaz
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Multilayer Perceptrons ◽  
Mineral Contents ◽  
Artificial Neural
Sign in / Sign up

Export Citation Format

Share Document