Effect of Thermomechanical Processing on Forming Limit Diagrams Predicted by Neural Networks

REFERENCES

• Boudeau , N. ; Gelin , J.C. ; Salhi , S. Computational prediction of the localized necking in sheet forming based on microstructural material aspects . Comp. Mater. Sci. 1998 , 11 , 45 – 64 .
   Google Scholar
• Moritoki , H. Criterion and mode of the forming limit in sheet forming . J. Mater. Process. Technol. 1992 , 3 , 363 – 378 .
   Google Scholar
• Banabic , D. ; Dorr , I.R. Prediction of the forming limit diagrams in pulsatory straining . J. Mater. Process. Technol. 1994 , 45 ( 1–4 ), 551 – 556 .
   Google Scholar
• Barata Da Rocha , A. ; Barlat , F. ; Jalinier , J.M. Prediction of the forming limit diagrams of anisotropic sheets in linear and nonlinear loading . Mater. Sci. Eng. 1985 , 68 , 151 – 164 .
   Google Scholar
• Son , H.S. ; Kim , Y.S. Prediction of forming limits for anisotropic sheets containing prolate ellipsoidal voids . Int. J. Mech. Sci. 2003 , 45 , 1625 – 1643 .
   Google Scholar
• Butuc , M.C. ; Barata da Rocha , A. ; Gracio , J.J. ; Ferreira Duarte , J. A more general model for forming limit diagrams prediction . J. Mater. Process. Technol. 2002 , 125–126 , 213 – 218 .
   Google Scholar
• Viatkina , E.M. ; Brekelmans , W.A.M. ; Geers , M.G.D. A crystal plasticity based estimate for forming limit diagrams from textural inhomogeneities . J. Mater. Process. Technol. 2005 , 168 , 211 – 218 .
   Google Scholar
• Stoughton , T.B. ; Zhu , X. Review of theoretical models of the strain-based FLD and their relevance to the stress-based FLD . Int. J. Plasticity 2004 , 20 , 1463 – 1486 .
   Web of Science ®Google Scholar
• Avila , A.F. ; Vieira , E.L.S. Proposing a better forming limit diagram prediction: a comparative study . J. Mater. Process. Technol. 2003 , 141 , 101 – 108 .
   Google Scholar
• Ozturk , F. ; Lee , D. Analysis of forming limits using ductile fracture criteria . J. Mater. Process. Technol. 2004 , 147 , 397–404.
   Google Scholar
• Bahrami , A. ; Mousavi Anijdan , S.H. ; Ekrami , A. Prediction of mechanical properties of DP steels using neural network model . J. Alloys Comp. 2005 , 392 , 177 – 182 .
   Web of Science ®Google Scholar
• Kurkova , V. Kolmogorov's theorem and multilayer neural networks . Neural Networks. 1992 , 5 , 501 – 506 .
   Web of Science ®Google Scholar
• Hornik , K. ; Stinchcombe , M. ; White , H. Multistage feedforward networks are universal approximators . Neural Networks 1989 , 5 , 501 – 506 .
   Google Scholar
• Guo , Z. ; Sha , W. Modeling the correlation between processing parameters and properties of maraging steels using artificial neural network . Comp. Mater. Sci. 2004 , 29 , 12 – 28 .
   Web of Science ®Google Scholar
• Yang , Y.Y. ; Linkens , D.A. ; Talamantes-Silva , J. Roll load prediction-data collection, analysis and neural network modeling . J. Mater. Process. Technol. 2004 , 152 , 304 – 315 .
   Google Scholar
• Leslie , W.C. The Physical Metallurgy of Steels ; McGraw Hill : London, England , 1982 .
   Google Scholar
• Humphreys , F.J. ; Hatherly , M. Recrystallization and Related Annealing Phenomena ; Pergamon Press : Sheffield, UK , 1996 .
   Google Scholar
• Roberts , W.L. Cold Rolling of Steel ; Marcel Dekker Inc. : New York, USA , 1978 .
   Google Scholar