Prediction of volume fractions in three-phase flows using nuclear technique and artificial neural network

Applied Radiation and Isotopes

Volumn 67, Issue 10, 2009, Pages 1812-1818

  Marques Salgado, César ^a   Brandão, Luis E B ^a   Schirru, Roberto ^b   Pereira, Cláudio M N A ^a   da Silva, Ademir Xavier ^b   Ramos, Robson ^a  

^a INSTITUTO DE PESQUISAS ENERGÉTICAS E NUCLEARES   (Brazil)

^b FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

Author keywords

Artificial neural network; Gamma rays; MCNP X; Volume fraction

Indexed keywords

ARTIFICIAL NEURAL NETWORK; DUAL-ENERGY; GAMMA RAY SOURCES; MCNP-X; NUCLEAR TECHNIQUES; OIL-WATER; THREE-PHASE FLOW; TRAINING DATA;

BACKPROPAGATION; GAS ABSORPTION; NEURAL NETWORKS; TITRATION; VOLUME FRACTION;

GAMMA RAYS;

OIL; PETROLEUM; WATER;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; FEASIBILITY STUDY; GAMMA RADIATION; GEOMETRY; METHODOLOGY; MONTE CARLO METHOD; PETROCHEMICAL INDUSTRY; PREDICTION; PRIORITY JOURNAL; RADIATION ABSORPTION; RADIATION SCATTERING;

EID: 69249223215     PISSN: 09698043     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apradiso.2009.02.093     Document Type: Article

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