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Thermal performance of Al2O3 nanoparticles dispersed in water was evaluated experimentally in a fully instrumented circular tube under turbulent flow conditions. Thermophysical properties of Al2O3 nanofluids at three different volumetric concentrations (0.38%, 0.81%, and 1.30%) were determined as a function of temperature. Pressure drop and heat transfer experiments were carried out at different volumetric concentrations and inlet fluid temperatures (10°C–30°C). The overall performance of the Al2O3 nanofluids was evaluated by considering both their hydraulic and heat transfer characteristics. The experimental results showed that the use of Al2O3 nanofluids increases the pressure drop by up to about 13% due to the greater viscosity. In addition, the heat transfer coefficient of nanofluids increased with the volumetric concentration by up to approximately 19% induced by the enhanced thermal conductivity. Furthermore, the experimental results indicated that the nanofluid with a volume fraction of 0.81% at the highest inlet fluid temperature increases the overall performance by up to around 8% and performs better than the other volume fractions. Enhancement in the overall performance increases with increasing inlet fluid temperature because of both the enhanced effective thermal conductivity and the decreased viscosity, which increases the energy exchange and decreases the pressure loss, respectively.

An experimental and analytical method to evaluate the performance of a loop-type wind turbine generator is presented. The loop-type wind turbine is a horizontal axis wind turbine with a different shaped blade. A computational fluid dynamics analysis and experimental studies were conducted in this study to validate the performance of the computational fluid dynamics method, when compared with the experimental results obtained for a 1/15 scale model of a 3 kW wind turbine. Furthermore, the performance of a full sized wind turbine is predicted. The computational fluid dynamics analysis revealed a sufficiently large magnitude of external flow field, indicating that no factor influences the flow other than the turbine. However, the experimental results indicated that the wall surface of the wind tunnel significantly affects the flow, due to the limited cross-sectional size of the wind tunnel used in the tunnel test. The turbine power is overestimated when the blockage ratio is high; thus, the results must be corrected by defining the appropriate blockage factor (the factor that corrects the blockage ratio). The turbine performance was corrected using the Bahaj method. The simulation results showed good agreement with the experimental results. The performance of an actual 3 kW wind turbine was also predicted by computational fluid dynamics.