April 16, 2024
Babak Aghel

Babak Aghel

Academic rank: Associate professor
Address: Department of Chemical Engineering, Faculty of Energy, Kermanshah University of Technology (KUT), Imam Khomeini Highway, Kermanshah, Iran
Education: Ph.D in Chemical Engineering
Phone: 083-38305000 (1168)
Faculty: Faculty of Engineering


Forecasting of water thermal conductivity enhancement by adding nano-sized alumina particles
Type Article
Thermal conductivity, Water-alumina nanofluids, Intelligent simulation, Generalized regression neural networks
Researchers Salah I. Yahya، Abbas Rezaei، Babak Aghel


Operating fluids play an important role in heat transfer equipment. Water is inexpensive popular operating fluid with extensive applications, but its thermophysical properties are not good enough, especially for high temperature processes. Therefore, modification of its inherent characteristics by adding nano-sized solid particles found high popularities. Thermal conductivity is one of the most important thermophysical properties of an operating fluid in relatively all energy-based processes. Variation of thermal conductivity of nanofluids with different operating conditions is required to be understood in such processes. Therefore, the focus of this study is concentrated on modeling of thermal conductivity of water-alumina nanofluids using four different smart paradigms. Multilayer perceptron, radial basis function, cascade feedforward, and generalized regression neural networks are employed for the considered task. The best structure of these paradigms is determined, and then, their accuracies are compared using different statistical indices. Accuracy analyses confirmed that the generalized regression neural network outperforms other considered smart methodologies. It predicted more than 280 experimental datasets with excellent absolute average relative deviation = 0.71%, mean square error = 0.0006, root mean square error = 0.023 and regression coefficient (R2) = 0.9675. In the final stage, the proposed paradigm is used for investigation of the effect of influential parameters on the thermal conductivity of water-alumina nanofluids. This type of accurate and straightforward paradigm can broaden our insight about thermal behavior of homogeneous suspension of nano-size alumina particles in water.