A comparative study on Arrhenius-type constitutive model and artificial neural network model to predict high-temperature deformation behaviour in Aermet100 steel
- 1 May 2011
- journal article
- Published by Elsevier BV in Materials Science and Engineering: A
- Vol. 528 (13-14), 4774-4782
- https://doi.org/10.1016/j.msea.2011.03.017
Abstract
No abstract availableFunding Information
- Chinese Aeronautics Fundamental Science Project Funds (03H53048)
This publication has 21 references indexed in Scilit:
- Prediction of the hot deformation behavior for Aermet100 steel using an artificial neural networkComputational Materials Science, 2010
- Research on the dynamic recrystallization kinetics of Aermet100 steelMaterials Science and Engineering: A, 2010
- Constitutive model for high temperature deformation of titanium alloys using internal state variablesMechanics of Materials, 2010
- A comparative study on Johnson Cook, modified Zerilli–Armstrong and Arrhenius-type constitutive models to predict elevated temperature flow behaviour in modified 9Cr–1Mo steelComputational Materials Science, 2009
- Grain size, strain rate, and temperature dependence of flow stress in ultra-fine grained and nanocrystalline Cu and Al: Synthesis, experiment, and constitutive modelingInternational Journal of Plasticity, 2009
- Constitutive equations to predict high temperature flow stress in a Ti-modified austenitic stainless steelMaterials Science and Engineering: A, 2009
- A dislocation-based constitutive law for pure Zr including temperature effectsInternational Journal of Plasticity, 2008
- Nanocrystalline aluminum and iron: Mechanical behavior at quasi-static and high strain rates, and constitutive modelingInternational Journal of Plasticity, 2006
- Microstructural based models for bcc and fcc metals with temperature and strain rate dependencyMechanics of Materials, 2005
- Behaviors of three BCC metal over a wide range of strain rates and temperatures: experiments and modelingInternational Journal of Plasticity, 1999