An Innovative Approach for Study of Thermal Behavior of an Unsteady Nanofluid Squeezing Flow between Two Parallel Plates Utilizing Artificial Neural Network
Hamid Haghshenas Gorgani 1, Peyman Maghsoudi 2 * , Sadegh Sadeghi 3
More Detail
1 Engineering Graphics Center, Sharif University of Technology, Tehran, IRAN2 School of Mechanical Engineering, College of Engineering, University of Tehran (UT), Amirabad, Tehran, IRAN3 School of Engineering, Iran University of Science and Technology, Tehran, IRAN* Corresponding Author


This study reveals the thermal behavior of an unsteady nanofluid streaming between two parallel plates by using artificial neural network (ANN). Initially, a similarity solution is employed to simplify the partial differential equations (PDSs) and convert them into a system of coupled nonlinear ordinary differential equations (ODEs). Subsequently, a numerical analysis is undertaken to verify the predicted results applying forth order Runge Kutta method. ANN is utilized to provide a nonlinear map between the considered input parameters such as solid volume fraction (Φ), Eckert number (Ec) and a moving parameter which represents the movement of the parallel plates (S), and output parameters like Nusselt number (Nu). Considering the accuracy of the current results, it is concluded that ANN method can be a potential reliable approach for function approximation. Results indicate that an optimal network with 16 neurons exists in hidden layer for which the value of RMSE for testing data is found to be 0.001364.


This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EUR J SUSTAIN DEV RES, 2019, Volume 3, Issue 1, Article No: em0069

Publication date: 06 Feb 2019

Online publication date: 31 Oct 2018

Article Views: 3979

Article Downloads: 1664

Open Access HTML Content References How to cite this article