Isothermal constant strain thermal compression test was carried out by Gleeble-3500 thermal simulation test machine. Based on the experimental data, the flow behavior of Ti-22Al-24Nb-0.5Y alloy was studied. The factors affecting the flow stress of the alloy were analyzed by orthogonal test, and a constitutive model based on BP neural network was established. The results show that the main factors affecting the flow stress of the alloy successively are the strain rate, deformation temperature and strain. The flow stress of Ti-22Al-24Nb-0.5Y alloy in hot deformation is more sensitive to the strain rate and the deformation temperature. The deformation of the alloy is characterized by flow softening at low deformation temperature and high strain rate, but the deformation tends to steady flow with high deformation temperature and low strain rate. The high temperature constitutive model of alloy established by BP neural network has high accuracy. The correlation coefficient reaches 0.9949, the average relative error is 3.23%, the predictive value with the deviation within 10% data points reaches up to 98.79%, and the prediction model can be used as a constitutive relation for the finite element simulation in Ti2AlNb based alloy plastic forming process.
LI S Q , MAO Y , ZHANG J W , et al. Effect of microstructure on tensile properties and fracture behavior of intermetallic Ti2AlNb alloys[J]. Transactions of Nonferrous Metals Society of China, 2002, 12 (4): 582- 586.
SHAGIEV M R , GALEYEV R M , VALIAKHMETOV O R , et al. Improved mechanical properties of Ti2AlNb-based intermeta-llic alloys and composites[J]. Advanced Materials Research, 2009, 59, 105- 108.
SHEN J , FENG A H . Recent advances on microstructural contr-olling and hot forming of Ti2AlNb-based alloys[J]. Acta Metall-urgica Sinica, 2013, 49 (11): 1286- 1294.
YAN J , PAN Q L , LI A D , et al. Flow behavior of Al-6.2Zn-0.70Mg-0.30Mn-0.17Zr alloy during hot compressive deforma-tion based on Arrhenius and ANN models[J]. Transactions of Nonferrous Metals Society of China, 2017, 27 (3): 638- 647.
CHEN H Q , LIN H , GUO L , et al. Hot deformation charact-eristics and constitutive relation of TC11 alloy[J]. Journal of Materials Engineering, 2007, (8): 32- 36.
焦李成. 神经网络系统理论[M]. 西安: 西安电子科技大学出版社, 1990.
JIAO L C . Neural network system theory[M]. Xi'an: Xidian University Press, 1990.
WANG K L , LU S Q , LI X , et al. A constitutive relation model for the Ti-6.5Al-3.5Mo-1.5Zr-0.3Si alloy based on BP neural network[J]. Special Casting & Nonferrous Alloys, 2008, 28 (8): 575- 578.
LIU X F , MA S J , LIU J P , et al. BP neural networks models for constitutive relationship during high temperature deformation process of Cu-12%Al alloy[J]. Journal of Materials Engineering, 2009, (1): 10- 14.
WANG Z , MAO F , HUANG X P , et al. Orthogonal test design for preparation of TiO2/graphene composites and study on its photocatalytic activity[J]. Rare Metals, 2011, 30 (Suppl 1): 271- 275.
JING L J , CUI G W , FENG Q , et al. Orthogonal test design for optimization of the extraction of polysaccharides from Lycium barbarum and evaluation of its anti-athletic fatigue activity[J]. Journal of Medicinal Plants Research, 2009, 3 (5): 433- 437.
YANG X , LIU C M , YI S L , et al. Orthogonal optimization test of vacuum diffusion welding of horizontally projected jet bits[J]. Journal of Oil and Gas Technology, 2007, 29 (5): 158- 160.
WANG K L , LU S Q , LI X , et al. Effects of temperature on flow stress and microstructure of TC11 alloy at high strain rate[J]. Special Casting & Nonferrous Alloys, 2008, 28 (3): 165- 167.
MURTY S V S N , RAO B N . On the flow localization concepts in the processing maps of titanium alloy Ti-24Al-20Nb[J]. Journal of Materials Processing Technology, 2000, 104 (1/2): 103- 109.
ZENG Z P , JONSSON S , ROVEN H J . The effects of defor-mation conditions on microstructure and texture of commercially pure Ti[J]. Acta Materialia, 2009, 57 (19): 5822- 5833.
REN Y J , WANG J W , ZHANG X B , et al. Prediction model of hot metal temperature for BF-BOF interface based on LM BP neural network[J]. Iron and Steel, 2012, 47 (9): 40- 42.