Prediction of the hot deformation behavior for Aermet100 steel using an artificial neural network

A one-parameter approach to determining the critical conditions for the initiation of dynamic recrystallization

Evgueni I. Poliak, John J. Jonas · Acta Materialia · 1996 · 951 citations

Materials Science, Engineering, Dynamic Constitutive Behavior +13

A dislocation-based constitutive law for pure Zr including temperature effects

Irene J. Beyerlein, C.N. Tomé · International Journal of Plasticity · 2007 · 647 citations

Materials Science, Materials Engineering, Engineering +12

Initiation of Dynamic Recrystallization in Constant Strain Rate Hot Deformation

Evgueni I. Poliak, J. J. Jonas · ISIJ International · 2003 · 455 citations · Full text

Engineering, Severe Plastic Deformation, Mechanical Engineering +19

Behaviors of three BCC metal over a wide range of strain rates and temperatures: experiments and modeling

Akhtar S. Khan, Riqiang Liang · International Journal of Plasticity · 1999 · 372 citations

Materials Science, Materials Engineering, Bcc Metal +11

Application of neural networks to predict the elevated temperature flow behavior of a low alloy steel

Y.C. Lin, Jun Zhang, Jue Zhong · Computational Materials Science · 2008 · 297 citations

Engineering, Machine Learning, Corrosion +9