Modeling thermal conductivity of ethylene glycol-based nanofluids using multivariate adaptive regression splines and group method of data handling artificial neural network-Reference-Cited by-同舟云学术

Modeling thermal conductivity of ethylene glycol-based nanofluids using multivariate adaptive regression splines and group method of data handling artificial neural network

Published:2020-01-01 Issue:1 Volume:14 Page:379-390
ISSN:1994-2060
Container-title:Engineering Applications of Computational Fluid Mechanics
language:en
Short-container-title:Engineering Applications of Computational Fluid Mechanics

Author:

Alotaibi Sorour¹,Amooie Mohammad Ali²,Ahmadi Mohammad Hossein³^ORCID,Nabipour Narjes⁴,Chau Kwok-wing⁵

Affiliation:

1. Mechanical Engineering Department, Faculty of Engineering and Petroleum, Kuwait University, Safat, Kuwait

2. School of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran

3. Faculty of Mechanical of Engineering, Shahrood University of Technology, Shahrood, Iran

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

5. Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, People’s Republic of China

Publisher

Informa UK Limited

Subject

Modelling and Simulation,General Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/19942060.2020.1715843

Reference46 articles.

1. Synthesis, characterization, thermal conductivity and sensitivity of CuO nanofluids

2. Using GMDH Neural Networks to Model the Power and Torque of a Stirling Engine

3. Application GMDH artificial neural network for modeling of Al2O3/water and Al2O3/Ethylene glycol thermal conductivity

4. A review of thermal conductivity of various nanofluids

5. Thermal conductivity ratio prediction of Al2O3/water nanofluid by applying connectionist methods

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