A comparison of artificial neural networks and symbolic-regression-based correlations for optimization of helically finned tubes in heat exchangers

Journal of Enhanced Heat Transfer

Volumn 18, Issue 2, 2011, Pages 115-125

  Zdaniuk, Gregory J ^a   Walters, D Keith ^b   Luck, Rogelio ^b   Chamra, Louay M ^b  

^a Ramboll UK   (United Kingdom)

^b MISSISSIPPI STATE UNIVERSITY   (United States)

Author keywords

Efficiency index; Friction; Heat transfer

Indexed keywords

ACCURATE PREDICTION; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; EFFICIENCY INDEX; EMPIRICAL CORRELATIONS; EXPERIMENTAL DATA; FINNED TUBE; FRICTION FACTORS; GENETIC PROGRAMMING TECHNIQUE; GEOMETRIC PARAMETER; HEAT TRANSFER ENHANCEMENT; OPERATING CONDITION; OPERATING PARAMETERS; OPTIMIZATION AND DESIGN; OPTIMIZATION PROCEDURES; OPTIMIZATION STUDIES; PARAMETER SPACES; REASONABLE VALUE; SKIMMING FLOWS; SYMBOLIC REGRESSION;

CORRELATION METHODS; EFFICIENCY; FRICTION; GENETIC PROGRAMMING; HEAT EXCHANGERS; HEAT TRANSFER; NEURAL NETWORKS; REGRESSION ANALYSIS; TRIBOLOGY; TUBES (COMPONENTS);

OPTIMIZATION;

EID: 79955691727     PISSN: 10655131     EISSN: None     Source Type: Journal    
DOI: 10.1615/JEnhHeatTransf.v18.i2.30     Document Type: Article

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