Determination of the Heat Transfer Coefficient of Metal Oxide Based Water Nanofluids in a Laminar Flow Regime Using an Adaptive Neuro-Fuzzy Inference System

摘要: In order to enhance the thermal properties of turbine oil (TO), three different nanoparticles (CuO, Al2O3, and TiO2) are loaded into TO. To measure performance nanoparticle-based TO nanofluids at laminar flow under constant heat flux boundary conditions, an experimental setup was applied. The obtained data clearly demonstrate positive effect all on transfer rate As most important factor, coefficient abovementioned two-phase systems is increased upon increasing both volume concentration rate. An adaptive neuro-fuzzy inference system (ANFIS) applied for modeling critical parameters nanoparticle-TO based numerically. results compared with ones training test data. suggest that developed model valid enough promising predicting extant coefficient. R2 MSE values...