Analytical Solutions of Heat Problems for Efficient Heat Transfer in a Nanofluid

Abstract

To find the approximate solutions of heat equations in a boundary layer flow, beneath a uniform free stream permeable continuous moving surface in a nanofluid is the main purpose of this paper. First, we will propose a neural network coupled with the Chebyshev polynomials. We will then study the heat transfer and heat flow equations by using the presented Chebyshev neural network. As it turns out, this method can obtain the approximate solutions for any kind heat transfer and heat flow equations. Approximate answers can be more helpful to study the behavior of heat transfer heat flow, and it can ensure a more efficient heat transfer with a lower operational cost. The missing slopes f rr(0) and gr(0), for some values of the governing parameters, namely the nano-particle volume fraction φ, the mov- ing parameter λ and the suction/injection parameter f0 are determined using the proposed method. The obtained results of this method have been compared with other papers results of different methods.