Aqueous nanofluids composed of alumina nanoparticles with different sizes at a concentration from 0.1vol% to 0.5vol% were prepared by a two-step method. The suspension and dispersion characteristics were experimentally examined by zeta potential, average size and absorption spectrum. The thermophysical properties such as the viscosity, surface tension, thermal conductivity, saturation vapor pressure and latent heat of vaporization were measured. The influences of the particle size, particle volume concentration and temperature on the thermophysical property were investigated. It was found that the viscosity and thermal conductivity increased with decreasing nanoparticle size. In contrast, the surface tension, saturation vapor pressure and latent heat of vaporization decrease with decreasing nanoparticle size. The viscosity, thermal conductivity and saturation vapor pressure have an increasing tendency with increasing volume concentration. However, surface tension and latent heat of vaporization showed a reverse tendency. Furthermore, the temperature also showed had obvious influence on the nanofluids viscosity, thermal conductivity and surface tension.

Thermal conductivities of two kinds of nanofluids (SiO2-water and SiO2-ethylene glycol) were measured by transient hot-wire method at different volume fraction and temperature. Influences of volume fraction of particles and temperature on thermal conductivities of nanofluids were analyzed. The Experimental results show that thermal conductivities of nanofluids are higher than those of base fluids, and increase with the increase of volume fraction and temperature. When approximately 0.5% volume fraction of SiO2nanoparticles are added into water and ethylene glycol at the temperature 50°C, the thermal conductivities are enhanced 46.2% and 62.8% respectively.

Al2O3-water nanofluids with volume concentration of 0.1%~0.5% were prepared by a two-step method, the thermophysical parameters such as thermal conductivity, viscosity and surface tension were measured, The results showed that the thermal conductivity of Al2O3-water nanofluids increased with increasing temperature and volume concentration, while the viscosity decreased with increasing temperature but increased with increasing volume concentration, in contrast to the thermal conductivity, the surface tension significantly decreased with increasing temperature and volume concentration. Furthermore, Al2O3-water nanofluids with 0.5% volume concentration were added into heat pipe. The experimental measurements showed that the Al2O3-water nanofluids have improved the heat transfer performance of heat pipe and the heat transfer coefficient of the heat pipe with Al2O3-water nanofluids enhanced by 85.7% when compared with the heat pipe with deionized water.

The oxide phosphor (Y1-xDyx)2O3(x=0-0.1) was obtained by calcining their respective precursors synthesized by homogeneous precipitation technique using rare earth nitrate as mother salt and urea as precipitating agent. The particle shape/size, fluorescent properties (especially the influence of Dy3+ concentration and calcination temperature) of the product was studied in detail. The results showed that the precursors exhibit monodisperse spherical morphology whose size can be controlled by adjusting the urea content. The phase pure (Y1-xDyx)2O3 can be obtained by calcining precursor at least 600 °C, and the monodisperse spherical morphology can be kept at even high temperature of 1000 °C. The (Y1-xDyx)2O3 phosphors exhibit strong yellow emission at ~577 nm (4F9/2→6H13/2 transition of Dy3+) and blue emission at ~491 nm (4F9/2→6H15/2 transition of Dy3+) upon optimal excitation wavelength of ~352 nm. The quenching concentration of Dy3+ was determined to be ~2 at% (x=0.02). The emission intensity of (Y1-xDyx)2O3 phosphors can be improved with the temperature and particle size increasing

Wavelet denoising method is applied in the measurement voltage signals in this paper. Noise reduction is important for signal preprocessing in order to achieve many objects such as the improvement of accuracy of modal analysis and electrical parameter identification, the effective extraction of features and auto-matic classification of different kinds of signals. The voltage signals measured from one 35Kv bus are used for the preprocessing research. The denoising effect is evaluated by three parameters, i.e. signal to noise ratio, mean squared error, and capture ability of step points. Compared with the traditional methods including mean filtering and medial filtering, wavelet method is superior in signal to noise ratio and mean squared error.