Artificial neural network techniques for the determination of condensation heat transfer characteristics during downward annular flow of R134a inside a vertical smooth tube

International Communications in Heat and Mass Transfer

Volumn 38, Issue 1, 2011, Pages 75-84

  Balcilar, M ^a   Dalkilic, A S ^a   Wongwises, S ^b  

^a YILDIZ TECHNICAL UNIVERSITY   (Turkey)

^b KING MONGKUT'S UNIVERSITY OF TECHNOLOGY THONBURI   (Thailand)

Author keywords

Condensation; Heat transfer coefficient; Modeling; Neural network; Pressure drop

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ANNULAR FLOWS; ARTIFICIAL INTELLIGENCE METHODS; ARTIFICIAL NEURAL NETWORK; BEST VALUE; CONDENSATION HEAT TRANSFER; CONTROL PARAMETERS; CONVECTIVE HEAT TRANSFER COEFFICIENT; CROSS VALIDATION; DATA POINTS; DIFFERENT MASS; DIFFERENTIAL PRESSURE TRANSDUCER; DOUBLE-TUBE HEAT EXCHANGER; ELIMINATION PROCESS; EXPERIMENTAL CONDITIONS; EXPERIMENTAL DATA; GENERALIZED REGRESSION NEURAL NETWORKS; IN-TUBE CONDENSATION; INNER DIAMETERS; INPUT VALUES; MASS FLUX; MODELING; MULTI LAYER PERCEPTRON; RADIAL BASIS NETWORKS; RELATIVE ERRORS; SATURATION TEMPERATURE; SMOOTH COPPER; SMOOTH TUBES; TEMPERATURE DIFFERENCES; TEST SECTIONS; TEST SETS; TRAINING PHASE; TRAINING SETS; TUBE WALLS; VALIDATION PROCESS; VAPOR QUALITY; WORKING FLUID;

ARTIFICIAL INTELLIGENCE; CONDENSATION; FUZZY INFERENCE; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; HEAT EXCHANGERS; HEAT FLUX; HEAT TRANSFER COEFFICIENTS; MULTILAYER NEURAL NETWORKS; PRESSURE DROP; RADIAL BASIS FUNCTION NETWORKS; TESTING; TRANSDUCERS; TUBES (COMPONENTS); WALLS (STRUCTURAL PARTITIONS);

HEAT CONVECTION;

EID: 78650292738     PISSN: 07351933     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.icheatmasstransfer.2010.10.009     Document Type: Article

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