TY - JOUR
ID - 22978
TI - The Smart Design Of Heat Exchangers With Expanded Surfaces By Genetic Algorithm And Image Processing
JO - Sharif Journal of Mechanical Engineering
JA - J40
LA - en
SN - 2676-4725
AU - Abolpour, B.
AU - Hekmatkhah, R.
AU - Ansari, A.B.
AD - Dept. of Chemical Engineering Sirjan University of Technology
AD - Faculty of New Sciences and Technologies, University of Tehran
AD - Dept. of Energy Graduate University of Advanced Technology, Kerman
Y1 - 2023
PY - 2023
VL - 39
IS - 2
SP - 25
EP - 35
KW - Nanofluid heat exchanger design
KW - expanded surfaces
KW - Computational Fluid dynamics
KW - Genetic Algorithm
KW - Image processing
DO - 10.24200/j40.2022.60770.1649
N2 - The analysis of heat transfer in the channel in many types of heat exchangers, such as electric cooling equipment, solar collectors, heat exchanger systems, high-performance boilers, gas turbine blade coolers, etc., is the basis of the design, construction, and optimization. Controlling heat transfer to increase the rate of heat transfer in such systems by improving the cooling method is an effective energy engineering from the point of saving energy. Increasing the heat transfer performance in the scales of macro and microchannels is crucial. The use of expanded surfaces in the channel is a practical method to increase the heat transfer coefficient. In the upcoming article, the smart design of a two-dimensional nanofluid heat exchanger has been studied numerically in order to achieve optimal performance conditions in terms of heat transfer rate, the amount of deposition of nanoparticles in the structure of the exchanger, as well as the fluid pressure drop while passing through it. It can be seen that the geometric structure optimized by the combination of genetic algorithm and computational fluid dynamics of this channel causes an increase of 1.14% in the enthalpy of the passing nanofluid, a decrease of 11.21% in the pressure drop of the passing nanofluid, and a reduction of 8.44% percentage in the deposition of nanoparticles inside the channel and a total increase of 24.82% in the fitting function defined in terms of these three variables, compared to the channel designed in previous studies. Therefore, this optimal channel has a higher heat transfer rate with a pressure drop and a lower amount of nanoparticle deposition compared to the previous channel, which proves the ability of the genetic algorithm with computational fluid dynamics in the optimal design of all types of heat exchangers.
UR - https://sjme.journals.sharif.edu/article_22978.html
L1 - https://sjme.journals.sharif.edu/article_22978_c66d9bfacca0c078ba7e34e35d7db71e.pdf
ER -