Turbulent flows in a spiral double-pipe heat exchanger Optimal performance conditions using an enhanced genetic algorithm

被引：77

作者：

Tian, Zhe ^{[1
]}

Abdollahi, Ali ^{[2
]}

Shariati, Mahmoud ^{[2
]}

Amindoust, Atefeh ^{[3
]}

Arasteh, Hossein ^{[4
]}

Karimipour, Arash ^{[2
]}

Goodarzi, Marjan ^{[5
]}

Bach, Quang-Vu ^{[5
]}

机构：

[1] Ocean Univ China, Sch Engn, Qingdao, Peoples R China

[2] Islamic Azad Univ, Najafabad Branch, Dept Mech Engn, Najafabad, Iran

[3] Islamic Azad Univ, Najafabad Branch, Dept Ind Engn, Najafabad, Iran

[4] Isfahan Univ Technol, Dept Mech Engn, Esfahan, Iran

[5] Ton Duc Thang Univ, Fac Environm & Labour Safety, Sustainable Management Nat Resources & Environm R, Ho Chi Minh City, Vietnam

来源：

INTERNATIONAL JOURNAL OF NUMERICAL METHODS FOR HEAT & FLUID FLOW | 2020年 / 30卷 / 01期

关键词：

Nanofluid; Optimization; Turbulent flow; Genetic algorithm; Heat exchanger; THERMAL-CONDUCTIVITY; TRANSFER COEFFICIENTS; SENSITIVITY-ANALYSIS; NANOFLUID FLOW; SLIP VELOCITY; LAMINAR-FLOW; NANOPARTICLES; FLUID; TEMPERATURE; MICROCHANNEL;

D O I：

10.1108/HFF-04-2019-0287

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

Purpose This paper aims to study the fluid flow and heat transfer through a spiral double-pipe heat exchanger. Nowadays using spiral double-pipe heat exchangers has become popular in different industrial segments due to its complex and spiral structure, which causes an enhancement in heat transfer. Design/methodology/approach In these heat exchangers, by converting the fluid motion to the secondary motion, the heat transfer coefficient is greater than that of the straight double-pipe heat exchangers and cause increased heat transfer between fluids. Findings The present study, by using the Fluent software and nanofluid heat transfer simulation in a spiral double-tube heat exchanger, investigates the effects of operating parameters including fluid inlet velocity, volume fraction of nanoparticles, type of nanoparticles and fluid inlet temperature on heat transfer efficiency. Originality/value After presenting the results derived from the fluid numerical simulation and finding the optimal performance conditions using a genetic algorithm, it was found that water-Al2O3 and water-SiO2 nanofluids are the best choices for the Reynolds numbers ranging from 10,551 to 17,220 and 17,220 to 31,910, respectively.

引用

页码：39 / 53

页数：15