Optimizing thermophysical properties of nanofluids using response surface methodology and particle swarm optimization in a non-dominated sorting genetic algorithm-Reference-Cited by-同舟云学术

Optimizing thermophysical properties of nanofluids using response surface methodology and particle swarm optimization in a non-dominated sorting genetic algorithm

Published:2019-10 Issue: Volume:103 Page:7-19
ISSN:1876-1070
Container-title:Journal of the Taiwan Institute of Chemical Engineers
language:en
Short-container-title:Journal of the Taiwan Institute of Chemical Engineers

Author:

Hemmat Esfe Mohammad,Kiannejad Amiri Mahmoud,Bahiraei Mehdi^ORCID

Publisher

Elsevier BV

Subject

General Chemical Engineering,General Chemistry

Reference63 articles.

1. Electronics cooling with nanofluids: a critical review;Bahiraei;Energy Convers Manag,2018

2. Enhancing thermal conductivity of fluids with nanoparticles;Choi;ASME Publ Fed,1995

3. Recent advances in modeling and simulation of nanofluid flows-Part I: fundamentals and theory;Mahian;Phys Rep,2019

4. Irreversibility characteristics of nanofluid flow under chaotic advection in a minichannel for different nanoparticle types;Bahiraei;J Taiwan Inst Chem Eng,2018

5. Thermal and hydraulic characteristics of a minichannel heat exchanger operated with a non-Newtonian hybrid nanofluid;Bahiraei;J Taiwan Inst Chem Eng,2018

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