Prediction of hydrothermal behavior of a non-Newtonian nanofluid in a square channel by modeling of thermophysical properties using neural network

This paper assesses the contribution of TiO2 nanoparticles on thermal performance of a 0.5 mass% aqueous solution of carboxymethyl cellulose (CMC) in a square channel. In this regard, a neural network model is firstly developed for modeling of power law index, consistency index, and thermal conductivity of the aqueous solution of TiO2/CMC-water non-Newtonian nanofluid in terms of the nanoparticle concentration and temperature. Then, an attempt is made to evaluate the friction factor and heat transfer coefficient relative values. According to the results, it is found that the friction factor ratio is directly proportional to the temperature and nanoparticle content, while it inversely varies relative to the shear rate. Moreover, heat transfer coefficient ratio is improved at elevated nanoparticle content, and this improvement is much more profound at higher temperature conditions. For practical purposes, the nanofluid hydrothermal performance index is examined since the addition of nanoparticles increases both heat transfer and friction factor. The corresponding data disclose that the performance index is directly proportional to the nanoparticle content, especially at decreased shear rate and elevated temperature conditions. The application of TiO2/CMC-water nanofluid is found to be more favorable for applications with elevated shear rate conditions.