Neural network modeling for the prediction of texture evolution of hot deformed aluminum alloys

Journal of Materials Engineering and Performance

Volumn 12, Issue 6, 2003, Pages 623-628

  Barat, P ^a   Withers, P J ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

Aluminum alloy; Gaussian process model; Neural network; Plane strain compression; Rolling

Indexed keywords

ALUMINUM ROLLING MILLS; ANNEALING; COMPUTER SIMULATION; DEFORMATION; NEURAL NETWORKS; OPTIMIZATION; PROCESS CONTROL; STRAIN RATE; TEMPERATURE; TEXTURES; THERMOMECHANICAL TREATMENT;

GAUSSIAN PROCESS MODEL; PLAIN STRAIN COMPRESSION TESTING;

ALUMINUM ALLOYS;

EID: 0347026176     PISSN: 10599495     EISSN: None     Source Type: Journal    
DOI: 10.1361/105994903322692402     Document Type: Article

References (14)

1. R.A. Ricks: Philos. Trans. R. Soc. London, 1999, Ser., A, 357, pp. 1513-29.
2. I. Gutierrez and M. Fuentes: "Influence of the Microstructural Changes Occurring During Steady State Hot Deformation on Static Recrystallization Kinetics and Recrystallized Grain Size of Commercial Aluminum," Recrystallization 90., Ed., T Chandra TMS, 1990 Warrendale, PA pp. 807-12.
3. N. Raghunathan, M.A. Zaidi, and T. Sheppard: "Recrystallization Kinetics of Al - Mg Alloys AA 5056 and AA 5083 After Hot Deformation," Mater. Sci. Technol., 1986, 2, pp. 938-45.
4. C.M. Sellers, A.M. Irisarri, and E.S. Puchi: "Recrystallization Characteristics of Aluminum - 1% Magnesium Under Hot Working Conditions" in Microstructural Control in Aluminum Alloys: Deformation, Recovery, and Recrystallization, E. Henry Chia and H.J. McQeen, ed., The Metallurgical Society/AIME, Warrendale, PA, 1986, pp. 179-96.
5. H.E. Vatne, T. Furu, R. Orsund, and E. Nes: "Modeling Recrystallization After Hot Deformation of Aluminum," Acta. Mater., 1996, 44, pp. 4463-73.
6. E.S. Puchi, J. Beynon, and C.M. Sellars: "Simulation of Hot Rolling Operations on Commercial Aluminum Alloys," Proc. Int. Conf. On Physical Metallurgy of Thermomechanical Processing of Steels and Other Metals: THERMC '88,. 1988, I. Tamura, ed., The Iron and Steel Institute of Japan, Tokyo, Japan, 1988, pp. 572-79.
7. P.D. Hodgson and R.K. Gibbs: "A Mathematical Model to Predict the Mechanical Properties of Hot Rolled C-Mn and Microalloyed Steels," ISIJ Int., 1992, 32, pp. 1329-38.
8. R. Sandstrom and R. Lagneborg: "A Model for Static Recrystallization After Hot Deformation," Acta Metall., 1975, 23, pp. 481-88.
9. T. Furu, H.R. Shercliff, G.J. Baxter, and C.M. Sellars: "The Influence of Transient Deformation Conditions on Recrystallization During Thermomechanical Processing of an Al-1% Mg Alloy," Acta Mater., 1999, 47, pp. 2377-89.
10. H.K.D.H. Bhadeshia, D.J.C. Mackay, and L.E. Svensson: "Impact Toughness of C-Mn Steel Arc Welds - Bayesian Neural Network Analysis," Mater. Sci. Technol., 1995, 11 (10), pp. 1046-51.
11. S.M. Roberts, J. Kusiak, Y.L. Liu, A. Forcellese, and P.J. Withers: "Prediction of Damage Evolution in Forged Aluminum Metal Matrix Composites Using a Neural Network Approach," J. Mater. Proc. Technol., 1998, 80-81, pp. 507-12.
12. G.J. Marshall: "Simulation of Commercial Hot Rolling by Laboratory Plane Strain Compression and its Application to Aluminum Industry Challenges." Proc. of the Second Symposium of Hot Deformation of Aluminum Alloys II, 1998, ed. T.R. Bieler, L.A. Lalli, and S.R. MacEwen, ed., The Minerals, Metals and Materials Society, Warrendale, PA, 1998, pp. 367-82.
13. D.J.C. Mackay: "Bayesian Interpolation," Neural Comput., 1992, 4, pp. 415-47.
14. D.J.C. Mackay: "Probable Networks and Plausible Predictions-a Review of Practical Bayesian Methods for Supervised Neural Networks," Network: Computat. Neural Syst., 1995, 6, pp. 469-505.