Prediction of Nanofluid Temperature Inside the Cavity by Integration of Grid Partition Clustering Categorization of a Learning Structure with the Fuzzy System-Reference-Cited by-同舟云学术

Prediction of Nanofluid Temperature Inside the Cavity by Integration of Grid Partition Clustering Categorization of a Learning Structure with the Fuzzy System

Published:2020-02-14 Issue:7 Volume:5 Page:3571-3578
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Nabipour Narjes¹,Babanezhad Meisam²,Taghvaie Nakhjiri Ali³^ORCID,Shirazian Saeed⁴⁵^ORCID

Affiliation:

1. Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam

2. Department of Energy, Faculty of Mechanical Engineering, South Tehran Branch, Islamic Azad University, 1584743311 Tehran, Iran

3. Department of Chemical Engineering, Science and Research Branch, Islamic Azad University, 1477893855 Tehran, Iran

4. Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam

5. Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.acs.org/doi/pdf/10.1021/acsomega.9b03911

Reference54 articles.

1. The Lid-Driven Cavity Flow: A Synthesis of Qualitative and Quantitative Observations

2. LAMINAR HEAT TRANSFER IN A TWO-DIMENSIONAL CAVITY COVERED BY A MOVING WALL

3. Effects of variable viscosity and thermal conductivity of Al2O3–water nanofluid on heat transfer enhancement in natural convection

4. Effect of sonication characteristics on stability, thermophysical properties, and heat transfer of nanofluids: A comprehensive review

5. The effect of membrane pores wettability on CO2 removal from CO2/CH4 gaseous mixture using NaOH, MEA and TEA liquid absorbents in hollow fiber membrane contactor

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