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Abstract: Micro- and nanoscale gas flows are analyzed theoretically and numerically. The analyses of gas flow similarity show that the gas flows at different scales can be similar only when the gas is treated as a prefect gas. If the gas density is so high that the density effect cannot be ignored, the three dimensionless parameters, Re, Ma, and Kn, which characterize the micro gas flow, are independent of each other and cannot be equal for flows at different scales, so the similarity breaks down. The critical density for the similarity failure can be analytically determined for each kind of gas. The analytical results were validated by numerical simulations. High density, high Knudsen number gas flows were modeled using a generalized Monte Carlo method based on the Enskog theory which considers both the density effect on the collision rate and the molecular repulsive and attractive interactions for a Lennard–Jones gas. The predicted transport coefficients agree better with experimental data than previous predictions. The simulation results show that when the gas density is higher than the critical density, the denseness effect alters the flow velocity and temperature fields from the direct simulation Monte Carlo results. Higher densities lead to greater deviation. [Copyright &y& Elsevier]

The lack of endurance is an important reason restricting further development of unmanned aerial vehicles (UAVs). Accurately estimating the state of charge (SOC) of the Li-Po battery can maximize the battery energy utilization and improve the endurance of UAVs. In this paper, the main current methods for estimating the SOC of vehicles were explored and discussed to unveil their advantages and disadvantages. In addition, the extended Kalman filter algorithm based on an equivalent circuit model was used to estimate SOC of power-type Li-Po batteries at different temperatures. The result showed that the closed-loop control method can effectively improve the battery life of small-sized electric UAVs. [ABSTRACT FROM AUTHOR]

The flame combustion processes involves chemical reactions and therefore flame stability is difficult to accurately assess. Based on flame radiation measuring parameters, a new synthetic evaluation system of flame combustion stability is established. A series of combustion conditions with various fuel/air ratios is investigated. Flame radiation luminance fluctuating information is acquired on a low-cost flame detection device. Power spectrum and bi-spectral information of the phase domain are derived from time domain signals based on Fourier transform and higher order statistics based upon a de-noising algorithm. The time–frequency characteristics and the features of the bi-spectrum under various combustion conditions are qualitatively analyzed, and the simultaneous descriptive parameters from time, frequency, and phase domain are extracted. A theoretical model for comprehensive fuzzy evaluation has been constructed, and also an index system has been established. It is demonstrated that this judgment system is reasonable and effective. The results can be used as an analyzing tool for process engineers for improving combustion conditions. [ABSTRACT FROM AUTHOR]