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Entropy generation minimization approach, quadratic optimization algorithm and artificial neural network (ANN) have been applied to find optimal condition of the turbulent Al 2 O 3 -60:40% EG/W nanofluid flow inside the absorber tube of a parabolic trough solar collector (PTSC). A three-input ANN has been employed for predicting optimal volume fraction ( ϕ opt ). The process is carried out for optimizing nanoparticle concentration, nanoparticle diameter, nanofluid average flow temperature and Reynolds number. Results show that the rate of the entropy generation decreases by decreasing volume fraction, increasing particle diameter and increasing average flow temperature. Adding the nanoparticles to the base-fluid increases frictional entropy generation and decreases thermal entropy generation. It causes an improvement in heat transfer but an increase in viscous irreversibility too. Finally, it was observed that for each particle sizes and average flow temperatures, there is a specific amount of optimal volume fraction, ϕ opt ; which is not dependent on the Re number. There is an optimal volume fraction for all Re numbers at constant particle size and mean flow temperature. Also, the optimum values of nanoparticle size, nanofluid average flow temperature and Reynolds number are found to be 90 nm, 360 K and 4000, respectively. [ABSTRACT FROM AUTHOR]

Abstract Corrugating channel walls is a way to enhance heat transfer in heat exchangers. In the current investigation, the entropy generation minimization approach has been employed to optimize heat transfer and fluid flow within a wavy channel. A numerical method has been built to compute entropy generation rate in a sinusoidal wavy-wall channel with copper-water (Cu-water) nanofluid flow. The governing equations have been discretized using finite volume method for a two-dimensional steady flow. The effects of geometrical and flow parameters, including nanoparticles volume fraction (0.01 < ϕ < 0.05), Richardson number (0.1 < Ri < 10), wave amplitude ratio (0.1 < α < 0.3) and wave length ratio (1 < λ < 3), have been investigated. Results reveal that increasing nanoparticle volume fraction within investigated Richardson number will increase Nusselt number. In addition, the maximum entropy generation rate declines as Richarson number increases. The optimal wave amplitude ratio (corresponding to lowest entropy generation), for wave length ratios of λ = 1 and λ = 2, found to be α = 0.2. Also, for wave length ratio of λ = 3, the minimum entropy generation approximately occurs at α = 0.1. Graphical abstract Unlabelled Image Highlights • Heat transfer of nanofluid flow inside sinusoidal wavy channels investigated. • A numerical method used to analyze the entropy generation rate for mixed convective heat transfer • Entropy generation minimization approach utilized for optimization. • Effects of geometrical parameters and nanoparticles concentration are investigated. • The optimal geometrical parameters for the channel are found. [ABSTRACT FROM AUTHOR]