scholarly journals Application of nanofluids for the optimal design of shell and tube heat exchangers using genetic algorithm

2016 ◽  
Vol 8 ◽  
pp. 198-206 ◽  
Author(s):  
Abazar Vahdat Azad ◽  
Nader Vahdat Azad
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Heat Exchangers ◽  
Shell And Tube

Globally Optimal Design of Intensified Shell and Tube Heat Exchangers using Complete Set Trimming

2021 ◽  
pp. 107644
Author(s):  
Chenglin Chang ◽  
Zuwei Liao ◽  
André L.H. Costa ◽  
Miguel J. Bagajewicz
Keyword(s):  
Optimal Design ◽  
Heat Exchangers ◽  
Complete Set ◽  
Shell And Tube

Optimal design of shell-and-tube heat exchangers

1994 ◽  
Vol 18 ◽  
pp. S295-S299 ◽  
Author(s):  
M. Reppich ◽  
J. Kohoutek
Keyword(s):  
Optimal Design ◽  
Heat Exchangers ◽  
Shell And Tube

Optimal Design of Heat Exchangers: A Genetic Algorithm Framework

1999 ◽  
Vol 38 (2) ◽  
pp. 456-467 ◽  
Author(s):  
Manish C. Tayal ◽  
Yan Fu ◽  
Urmila M. Diwekar
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Heat Exchangers ◽  
Algorithm Framework

Experimental Study and Genetic-Algorithm-Based Correlation on Shell-Side Heat Transfer and Flow Performance of Three Different Types of Shell-and-Tube Heat Exchangers

2006 ◽  
Vol 129 (9) ◽  
pp. 1277-1285 ◽  
Author(s):  
Qiu-wang Wang ◽  
Gong-nan Xie ◽  
Bo-tao Peng ◽  
Min Zeng
Keyword(s):  
Heat Transfer ◽  
Genetic Algorithm ◽  
Heat Exchanger ◽  
Pressure Drop ◽  
Heat Exchangers ◽  
Transfer Coefficients ◽  
Shell Side ◽  
Heat Transfer Coefficients ◽  
Friction Factors ◽  
Shell And Tube

The heat transfer and pressure drop of three types of shell-and-tube heat exchangers, one with conventional segmental baffles and the other two with continuous helical baffles, were experimentally measured with water flowing in the tube side and oil flowing in the shell side. The genetic algorithm has been used to determine the coefficients of correlations. It is shown that under the identical mass flow, a heat exchanger with continuous helical baffles offers higher heat transfer coefficients and pressure drop than that of a heat exchanger with segmental baffles, while the shell structure of the side-in-side-out model offers better performance than that of the middle-in-middle-out model. The predicted heat transfer rates and friction factors by means of the genetic algorithm provide a closer fit to experimental data than those determined by regression analysis. The predicted corrections of heat transfer and flow performance in the shell sides may be used in engineering applications and comprehensive study. It is recommended that the genetic algorithm can be used to handle more complicated problems and to obtain the optimal correlations.

Use of genetic algorithms for the optimal design of shell-and-tube heat exchangers

2009 ◽  
Vol 29 (2-3) ◽  
pp. 203-209 ◽  
Author(s):  
José M. Ponce-Ortega ◽  
Medardo Serna-González ◽  
Arturo Jiménez-Gutiérrez
Keyword(s):  
Genetic Algorithms ◽  
Optimal Design ◽  
Heat Exchangers ◽  
Shell And Tube

Optimal Design of Shell-and-Tube Heat Exchangers Using Particle Swarm Optimization

2009 ◽  
Vol 48 (6) ◽  
pp. 2927-2935 ◽  
Author(s):  
Mauro A. S. S. Ravagnani ◽  
Aline P. Silva ◽  
Evaristo C. Biscaia ◽  
Jose A. Caballero
Keyword(s):  
Particle Swarm Optimization ◽  
Optimal Design ◽  
Heat Exchangers ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Shell And Tube
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