A comparative study on Arrhenius-type constitutive model and artificial neural network model to predict high-temperature deformation behaviour in Aermet100 steel

Materials Science and Engineering: A

Volumn 528, Issue 13-14, 2011, Pages 4774-4782

  Ji, Guoliang ^a,b   Li, Fuguo ^b   Li, Qinghua ^b   Li, Huiqu ^c   Li, Zhi ^c  

^a HENAN POLYTECHNIC UNIVERSITY   (China)

^b NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^c BEIJING INSTITUTE OF AERONAUTICAL MATERIALS   (China)

Author keywords

Aermet100; Artificial neural network; Constitutive model

Indexed keywords

COMPRESSION TESTING; COMPUTER SYSTEM RECOVERY; DEFORMATION; DYNAMIC RECRYSTALLIZATION; DYNAMICS; HOT WORKING; NEURAL NETWORKS; RECOVERY; STABILITY; STRAIN HARDENING; STRAIN RATE;

AERMET100; ARRHENIUS; ARTIFICIAL NEURAL NETWORK MODELING; COMPARATIVES STUDIES; FEEDFORWARD BACKPROPAGATION; GLEEBLE; HIGH TEMPERATURE DEFORMATION BEHAVIOR; HOT-COMPRESSION TESTS; RELATIVE ERRORS; STRESS-STRAIN DATA;

CONSTITUTIVE MODELS;

EID: 79953289307     PISSN: 09215093     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.msea.2011.03.017     Document Type: Article

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