Thermal performance of energy systems can be improved by adding metal or metal-oxide nanoparticles to a base fluid, thereby increasing heat-transfer efficiency. Laminar pipe flow of a Cu–water nanofluid was studied using discrete phase model numerical simulation and experimental methods. The forces including thermophoretic and Brownian forces were considered to solve the particles governing equation. A two-step method was employed in the preparation of the nanofluid. The influences of Reynolds number, fluid temperature, and particle volume fraction on the flow pressure drop and convective heat-transfer coefficient of the nanofluid have been studied. The results demonstrated that adding nanoparticles to a base fluid significantly enhanced convective heat transfer in a pipe and increased energy loss. The pressure drop increased with increasing Reynolds number. A critical nanoparticle volume fraction existed, beyond which the pressure drop changed from increasing to decreasing with increasing nanoparticle volume fraction. This is attributed to competition between slip of particles on the pipe wall and the effect of a drag force on the particles. The deposition efficiency of nanoparticle changing with the particle size and volume fraction also has been illustrated.

Blades in strong wind conditions are prone to various failures and damage that is due to the action of random variable amplitude loads. In this study, we analyze the failure of 1.5 MW horizontal axis wind turbine blades. The computational fluid dynamics unsteady calculation method is used to simulate the aerodynamic load distribution on the blade. Fluid–structure coupling methods are applied to calculate the blade stress. The results show that the equivalent stress of the blade is the largest when the azimuth angle is 30°, and the maximum equivalent stress is 20.60 MPa. There are obvious stress peaks in six sections, such as r/R = 0.10 (the span length of blade/the full length of the blade = 0.10). The frequency of damage that is caused by the stress in each area of the blade is determined based on the blade damage. The frequency of gel coat cracking in the blade tips and leaves is 77.78% and 22.22%, respectively, and the frequency of crack occurrence is 87.75%, 10.20% and 2.05%, respectively. By combining the stress concentration area and the damage results, the cause of blade damage is determined, which can replace the traditional inspection methods and improve the inspection efficiency.

In this paper, the effect of melting characteristics of CuO/paraffin wax composite phase change material in a spherical heat storage unit in a constant temperature water bath is investigated. Experiments were conducted in three different water bath temperatures (65 °C, 70 °C, and 75 °C). The inner surface of the sphere was fixed with two, four, and six pin-shaped fins 3 mm in diameter. The spheres were filled with different mass fractions of CuO nanoparticles/paraffin phase change materials. Experimental CCD was used to model and optimize the spherical thermal storage unit. Regression models were developed to predict the effects of various operational factors on the melting time of the composite PCM. The factors in the model included the number of pin fins in the spherical heat storage unit, the water bath temperature, and the content of added CuO nanoparticles in the PCM, and ANOVA was used to statistically validate the regression model. The results showed that the interaction between the water bath temperature and the number of pin fins had the most significant effect on the melting time. With the melting time of the phase change material as the optimized objective function, the optimized optimal working condition was six pin fins, a water bath temperature of 75 °C, and the addition of 5 wt% CuO nanoparticles/paraffin phase change material, and the actual melting time under this condition was 78.9 min, which was lower than the predicted value of 79.4 min, with an error of 0.63% between them.