Prediction of compressive properties of closed-cell aluminum foam using artificial neural network

Computational Materials Science

Volumn 43, Issue 4, 2008, Pages 767-773

  Raj, R Edwin ^a   Daniel, B S S ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY ROORKEE   (India)

Author keywords

Aluminum foam; ANN; Closed cell foam; Mechanical properties; Modeling

Indexed keywords

ABSORPTION; ALUMINA; ALUMINUM; ALUMINUM POWDER METALLURGY; BACKPROPAGATION; COMPRESSION TESTING; IMAGE CLASSIFICATION; LIGHT METALS; NETWORK PROTOCOLS; PARALLEL PROCESSING SYSTEMS; SENSOR NETWORKS; STRAIN RATE;

ALUMINUM FOAM; ANN; CLOSED-CELL FOAM; MECHANICAL PROPERTIES; MODELING;

NEURAL NETWORKS;

EID: 53149103587     PISSN: 09270256     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.commatsci.2008.01.041     Document Type: Article

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