Soft computing method for prediction of co2 corrosion in flow lines based on neural network approach

Chemical Engineering Communications

Volumn 200, Issue 6, 2013, Pages 731-747

  Chamkalani, Ali ^a   Nareh'ei, Milad Arabloo ^b   Chamkalani, Reza ^c   Zargari, Mohammad Hadi ^a   Dehestani Ardakani, Mohammad Reza ^a   Farzam, Mansoor ^a  

^a PETROLEUM UNIVERSITY OF TECHNOLOGY   (Iran)

^b SHARIF UNIVERSITY OF TECHNOLOGY   (Iran)

^c BU ALI SINA UNIVERSITY   (Iran)

Author keywords

Artificial neural network; CO2 corrosion; Partial pressure; pH; Sensitivity analysis; Temperature; Velocity

Indexed keywords

CORROSION PREDICTION; EXPERIMENTAL DATUM; INPUT VARIABLES; OIL/GAS WELLS; OPERATIONAL PARAMETERS; PREDICTIVE MODELS; PRODUCTION FLOWS; RATE OF CORROSIONS; RATE PREDICTIONS; SOFT COMPUTING METHODS; STATISTICAL ERROR ANALYSIS; THEORETICAL MODELS;

CARBON DIOXIDE; ERROR ANALYSIS; FORECASTING; NEURAL NETWORKS; PARTIAL PRESSURE; PH; SENSITIVITY ANALYSIS; SOFT COMPUTING; TEMPERATURE; VELOCITY;

CORROSION RATE;

EID: 84873665635     PISSN: 00986445     EISSN: 15635201     Source Type: Journal    
DOI: 10.1080/00986445.2012.717311     Document Type: Article

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