ABSTRACT In this paper, based on the analysis of oil sludge composition and environmental hazards, the microwave catalytic pyrolysis of oil sludge for recovering combustible gas and chain hydrocarbon light oil disposal process, is proposed to perform the recycling of oil sludge and reduce the risk of environmental pollution. In order to improve the yield of combustible gas and light oil in oil sludge pyrolysis, the impact of adding four catalysts (nano-CuO, nano-NiO, nano-MgO, and nano-γ-Al2O3) on the heating characteristics of oil sludge and the composition and quality of products during microwave pyrolysis, were experimentally studied and analyzed. The results show that the catalyst can increase the heating rate of sludge and the yield of pyrolysis oil and gas. The increasing order of heating is: nano-CuO > nano-γ-Al2O3 > nano-MgO > nano-NiO > blank group. Compared with the blank group, the content of combustible gas (H2 + CH4 + CO) increases by 18.824wt% (MgO), 4.511wt% (CuO), 9.28wt% (NiO), and 16.164wt% (γ-Al2O3), respectively. It can be deduced that nano-metal oxide catalysts, especially γ-Al2O3, can promote the decomposition of oil sludge, improve the content of low carbon straight chain hydrocarbons and alcohols, and improve the quality of pyrolysis oil products.

ABSTRACT The cavitation phenomenon is an important factor affecting the safe and stable operation of hydraulic machinery units. The cavitation of the hydraulic machinery units can lead to the increased vibration, reduced efficiency, and cavitation erosion of blades. Therefore, a method is needed to determine the incipient cavitation of hydraulic machinery runner blades. This study is initiated from the acoustic characteristics of bubbles generated by the cavitation of model hydraulic turbines and the characteristics of radiated sound energy during cavitation. The characteristics of cavitation noise are studied. After the qualitative analysis of the high- and low-frequency energy distribution patterns of cavitation noise signals before and after cavitation, a mathematical model of the time-frequency characteristics of these signals is proposed using the energy distribution analysis method. The feature information is extracted from the cavitation noise signals and used to judge the occurrence of incipient cavitation in model turbine runner blades. Based on this method, an online cavitation monitoring system is constructed, and comparative tests are carried out on a model pump turbine and Francis turbine. It is found that the results of the proposed method for the judgment of incipient cavitation are highly consistent with those of traditional methods. vibration efficiency blades Therefore studied high lowfrequency low frequency timefrequency time constructed methods

ABSTRACT The annual output of refinery waste sludge is huge in our country, and the resource disposal of sludge has become a difficult problem that needs to be overcome. In order to increase the content of renewable gas and light oil after pyrolysis of oil sludge at the bottom of refinery tank, nano-CuO and nano-γ-Al2O3 with good wave-absorbing property and good catalytic property were selected to study the effect of additive load on the characteristics of pyrolysis reaction products by experimental research and analysis. The results show that the highest oil and gas yields can be obtained when the nano-CuO content is 10%. When nano-γ-Al2O3 was loaded at 15%, the pyrolysis oil and pyrolysis gas yield reached the peak. Moreover, the light component of pyrolysis oil can be improved, and the proportion of gasoline and diesel (C4 ~ C12, C13 ~ C18) is 75.422%. H2 volume content reaches the highest at 15% load.