Development of constitutive relationship model of Ti600 alloy using artificial neural network

Computational Materials Science

Volumn 48, Issue 3, 2010, Pages 686-691

  Sun, Y ^a   Zeng, W D ^a   Zhao, Y Q ^b   Qi, Y L ^a,b   Ma, X ^a   Han, Y F ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b NORTHWEST INSTITUTE FOR NONFERROUS METAL RESEARCH   (China)

Author keywords

BP neural network; Constitutive relationship; Ti600 alloy

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BACK-PROPAGATION NEURAL NETWORKS; BP NEURAL NETWORKS; COMPARATIVE EVALUATIONS; CONSTITUTIVE RELATIONSHIP; CONSTITUTIVE RELATIONSHIP MODEL; CONSTITUTIVE RELATIONSHIPS; DEFORMATION TEMPERATURES; ESTABLISHED NETWORKS; EXPERIMENT DATA; FINITE ELEMENT SIMULATIONS; FLOW STRESS; GLEEBLE-1500 THERMAL SIMULATOR; NETWORK MODELS; NON-LINEAR RELATIONSHIPS; PREDICTION MODEL; REGRESSION METHOD; TRUE STRAIN;

ALLOYS; BACKPROPAGATION; DATA COMPRESSION; DATA FLOW ANALYSIS; DEFORMATION; FINITE ELEMENT METHOD; FUNCTIONS; MATHEMATICAL MODELS; PLASTIC FLOW; STRAIN RATE;

NEURAL NETWORKS;

EID: 77950948549     PISSN: 09270256     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.commatsci.2010.03.007     Document Type: Article

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