Modeling of constitutive relationships and microstructural variables of Ti-6.62Al-5.14Sn-1.82Zr alloy during high temperature deformation

Materials Characterization

Volumn 59, Issue 10, 2008, Pages 1386-1394

  Luo, Jiao ^a   Li, Miaoquan ^a   Hu, Yiqu ^a   Fu, M W ^b  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Constitutive relationship; Fuzzy neural network; Grain size; Titanium alloy; Volume fraction

Indexed keywords

ALLOYS; ALUMINUM; BACKPROPAGATION; DEFORMATION; FOOD PROCESSING; FORECASTING; FUZZY SETS; LEARNING ALGORITHMS; LEARNING SYSTEMS; NEURAL NETWORKS; PLASTIC FLOW; SET THEORY; TIN; TIN ALLOYS; TITANIUM; ZIRCONIUM; ZIRCONIUM ALLOYS;

ARTIFICIAL NEURAL NETWORK; BACK-PROPAGATION LEARNING ALGORITHM; CONSTITUTIVE RELATIONSHIP; CONSTITUTIVE RELATIONSHIPS; EXPERIMENTAL DATA; FLOW STRESSES; FUZZY NEURAL NETWORK; GRAIN SIZE; GRAIN SIZES; HIGH-TEMPERATURE DEFORMATION; ISOTHERMAL COMPRESSIONS; MICROSTRUCTURAL VARIABLES; QUANTITATIVE METALLOGRAPHY; REGRESSION METHODS; TITANIUM ALLOY; VOLUME FRACTION;

TITANIUM ALLOYS;

EID: 49949098616     PISSN: 10445803     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.matchar.2007.12.005     Document Type: Article

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