The fuzzy neural network model of flow stress in the isothermal compression of 300M steel

Materials and Design

Volumn 41, Issue , 2012, Pages 83-88

  Liu, Y G ^a   Luo, J ^a   Li, M Q ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

Ferrous metals; Flow stress; Fuzzy neural network; Isothermal compression; Model

Indexed keywords

BACKPROPAGATION LEARNING ALGORITHM; DEFORMATION TEMPERATURES; FERROUS METALS; FUZZY NEURAL NETWORK MODEL; FUZZY-NEURAL; ISOTHERMAL COMPRESSIONS; REGRESSION METHOD; REGRESSION MODEL; STRESS DECREASE;

DEFORMATION; FUZZY NEURAL NETWORKS; ISOTHERMS; LEARNING ALGORITHMS; MODELS; REGRESSION ANALYSIS; STRAIN RATE;

PLASTIC FLOW;

EID: 84861127238     PISSN: 02641275     EISSN: 18734197     Source Type: Journal    
DOI: 10.1016/j.matdes.2012.04.043     Document Type: Article

References (20)

1. Momeni A., Dehghani K. Characterization of hot deformation behavior of 410 martensitic stainless steel using constitutive equations and processing maps. Mater Sci Eng A 2010, 527:5467-5473.
2. Yuan H., Liu W.C. Effect of the δ phase on the hot deformation behavior of Inconel 718. Mater Sci Eng A 2005, 408:281-289.
3. Niu Y., Hou H.L., Li M.Q., Li Z.Q. High temperature deformation behavior of a near alpha Ti600 titanium alloy. Mater Sci Eng A 2008, 492:24-28.
4. Wang Y., Shao W.Z., Zhen L., Yang L., Zhang X.M. Flow behavior and microstructures of superalloy 718 during high temperature deformation. Mater Sci Eng A 2008, 497:479-486.
5. Li M.Q., Pan H.S., Lin Y.Y., Luo J. High temperature deformation behavior of near alpha Ti-5.6Al-4.8Sn-2.0Zr alloy. J Mater Process Technol 2007, 183:71-76.
6. Niu Y., Luo J., Li M.Q. An adaptive constitutive model in the isothermal compression of Ti600 alloy. Mater Sci Eng A 2010, 527:5924-5929.
7. Li M.Q., Liu X.M., Xiong A.M. Prediction of the mechanical properties of forged TC11 titanium alloy by ANN. J Mater Process Technol 2002, 121:1-4.
8. Yu W.X., Li M.Q., Luo J., Su S.B., Li C.Q. Prediction of the mechanical properties of the post-forged Ti-6Al-4V alloy using fuzzy neural network. Mater Des 2010, 31:3282-3288.
9. Kumar S., Kumar S., Prakash, Shankar R., Tiwari M.K., Kumar S.B. Prediction of flow stress for carbon steels using recurrent self-organizing neuro fuzzy networks. Expert Syst Appl 2007, 32:777-788.
10. Luo J., Li M.Q., Yu W.X. Prediction of flow stress in isothermal compression of Ti-6Al-4V alloy using fuzzy neural network. Mater Des 2010, 31:3078-3083.
11. Chen D.J., Li M.Q., Wu S.C. Modeling of microstructure and constitutive relation during superplastic deformation by fuzzy-neural network. J Mater Process Technol 2003, 142:197-202.
12. Niu Y., Luo J., Li M.Q. The correlation model between the hydrogen content and the flow stress in the isothermal compression of Ti600 alloy. Int J Hydrogen Energy 2011, 36:1006-1013.
13. Samantaray D., Mandal S., Bhaduri A.K. Constitutive analysis to predict high-temperature flow stress in modified 9Cr-1Mo (P91) steel. Mater Des 2010, 31:981-984.
14. Senthilkumar V., Balaji A., Narayanasamy R. Analysis of hot deformation behavior of Al 5083-TiC nanocomposite using constitutive and dynamic material models. Mater Des 2012, 37:102-110.
15. Abbasi S.M., Shokuhfar A. Prediction of hot deformation behaviour of 10Cr-10Ni-5Mo-2Cu steel. Mater Lett 2007, 61:2523-2526.
16. Cai J., Li F.G., Liu T.Y., Chen B., He M. Constitutive equations for elevated temperature flow stress of Ti-6Al-4V alloy considering the effect of strain. Mater Des 2011, 32:1144-1151.
17. Liang X.P., Liu Y., Li H.Z., Zhou C.X., Xu G.F. Constitutive relationship for high temperature deformation of powder metallurgy Ti-47Al-2Cr-2Nb-0.2W alloy. Mater Des 2012, 37:40-47.
18. Luo J., Li M.Q., Hu Y.Q., Fu M.W. Modeling of constitutive relationships and microstructural variables of Ti-6.62Al-5.14Sn-1.82Zr alloy during high temperature deformation. Mater Charact 2008, 59:1386-1394.
19. Kalaichelvi V., Sivakumar D., Karthikeyan R., Palanikumar K. Prediction of the flow stress of 6061 Al-15%SiC-MMC composites using adaptive network based fuzzy inference system. Mater Des 2009, 30:1362-1370.
20. Jia W.J., Zeng W.D., Han Y.F., Liu J.R., Zhou Y.G., Wang Q.J. Prediction of flow stress in isothermal compression of Ti60 alloy using an adaptive network-based fuzzy inference system. Mater Des 2011, 32:4676-4683.