Fluid flow characteristics for shell side of double-pipe heat exchanger with helical fins and pin fins

2012 ◽  
Vol 36 ◽  
pp. 30-43 ◽  
Author(s):  
Li Zhang ◽  
Wenjuan Du ◽  
Jianhua Wu ◽  
Yaxia Li ◽  
Yanwei Xing
Keyword(s):  
Fluid Flow ◽  
Heat Exchanger ◽  
Flow Characteristics ◽  
Shell Side ◽  
Pin Fins ◽  
Fluid Flow Characteristics ◽  
Double Pipe ◽  
Pipe Heat

Application of Genetic Algorithm-Polynomial Neural Network for Modelling Heat Transfer and Fluid Flow Characteristics of a Double-Pipe Heat Exchanger

2013 ◽  
Author(s):  
Mehdi Mehrabi ◽  
Tuhid Pashaee ◽  
Mohsen Sharifpur ◽  
Josua P. Meyer
Keyword(s):  
Neural Network ◽  
Heat Transfer ◽  
Genetic Algorithm ◽  
Fluid Flow ◽  
Heat Exchanger ◽  
Flow Characteristics ◽  
Primary Data ◽  
Polynomial Neural Network ◽  
Fluid Flow Characteristics ◽  
Double Pipe

In this paper a genetic algorithm-polynomial neural network approach is used in order to model the effect of important parameters on heat transfer as well as fluid flow characteristics for a double-pipe helical heat exchanger by using numerical-certified results. In this way, overall heat transfer coefficient (Uo), inner and annular pressure drop (ΔPin, ΔPan) are modeled with respect to the variation of inner and annular dean number, inner and annular Prandtl number, and pitch of coil which are defined as input (design) variables. The numerical-certified data was randomly divided into test and train sections which the former is used for benchmark. The GA-PNN structure was instructed by 75 percent of the numerical-validated data. 25 percent of the primary data which had been considered for testing procedure were entered into GA-PNN proposed models and results were compared by statistical criteria.

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