A comparative study on constitutive relationship of as-cast 904L austenitic stainless steel during hot deformation based on Arrhenius-type and artificial neural network models

Computational Materials Science

Volumn 67, Issue , 2013, Pages 93-103

  Han, Ying ^a   Qiao, Guanjun ^a   Sun, Jiapeng ^a   Zou, Dening ^b  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY   (China)

Author keywords

Arrhenius type; Artificial neural network; Austenitic stainless steel; Constitutive relationship; Hot deformation

Indexed keywords

ARRHENIUS-TYPE; ARTIFICIAL NEURAL NETWORK MODELS; AS-CAST; AVERAGE ERRORS; BACK-PROPAGATION NEURAL NETWORKS; BP NEURAL NETWORK MODEL; BP NEURAL NETWORKS; COMPARATIVE STUDIES; COMPRESSIVE DEFORMATION BEHAVIOR; CONSTITUTIVE RELATIONSHIPS; CORRELATION COEFFICIENT; DEFORMATION CONDITIONS; ELEVATED TEMPERATURE; HOT COMPRESSION TESTS; STATISTICAL PARAMETERS; STRAIN DATA; STRAIN EFFECT; TEMPERATURE COMPENSATION; TEMPERATURE RANGE; THERMO-MECHANICAL;

COMPRESSION TESTING; DEFORMATION; HOT WORKING; NEURAL NETWORKS; STRAIN RATE; STRESSES;

AUSTENITIC STAINLESS STEEL;

EID: 84870026317     PISSN: 09270256     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.commatsci.2012.07.028     Document Type: Article

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