Effect of Ammonia on Laminar Combustion Characteristics of Methane-Air Flames at Elevated Pressures.

In this paper, laminar combustion characteristics of methane/ammonia/air flames are numerically investigated using the Chemkin/Premix code. The initial temperature is set as 298 K; the initial pressures are set as 1, 2, 5, 10, and 20 atm; and the equivalence ratios are set as 0.8-1.6. Laminar burning velocity (LBV); adiabatic flame temperature (AFT); net heat release rate (NHRR); and the mole fractions of H, NH2, NO, NO2, and HCN at stoichiometric ratio are studied with ammonia (NH3) addition. Meanwhile, temperature sensitivity and rate of production (ROP) are analyzed. The results show that with the increase of the initial pressures, LBV decreases and AFT and NHRR increase. With the increase of ammonia doping ratios, LBV, AFT, and NHRR decrease. From temperature sensitivity analyses, the main reactions that promote temperature rise are R39 (H + O2 < = > O + OH), R100 (OH + CH3 < = > CH2(S) + H2O), R102 (OH + CO < = > H + CO2), and R122 (HO2 + CH3 < = > OH + CH3O). The main reactions that inhibit temperature rise are R53 (H + CH3(+M) < = > CH4(+M)), R36 (H + O2 + H2O < = > HO2 + H2O), and R46 (H + HO2 < = > O2 + H2). For the rate of production of the free radical pool, the trends of H and NO are consuming first and then producing, and the trends of NH2, NO2, and HCN are the opposite. The pathway from methane to carbon dioxide is CH4 → CH3 → CH3O → CH2O → HCO → CO → CO2, and the pathway from ammonia to nitrogen is NH3 → NH2 → NH/HNO → NO/NO2 → N2.

VR motion sickness recognition by using EEG rhythm energy ratio based on wavelet packet transform.

BACKGROUND AND OBJECTIVES: Virtual reality motion sickness (VRMS) is one of the main factors hindering the development of VR technology. At present, the VRMS recognition methods using electroencephalogram (EEG) signals have poor applicability to multiple subjects. METHODS: Aiming at this dilemma, the wavelet packet transform (WPT), was used to propose a feature extraction method for EEG rhythm energy ratios of delta (δ), theta (θ), alpha (α), and beta (ß) in this research. Moreover, VRMS was recognized by combining k-Nearest Neighbor classifier (k-NN), support vector machine (SVM) with polynomial kernel (polynomial-SVM) and radial basis function kernel (RBF-SVM), respectively. The method is that the raw EEG signals were de-noised by an elliptical band-pass filter and segmented by a fixed window, 7-level db4 WPT was performed on each EEG segment, and the wavelet packet energy ratios of delta, theta, alpha and beta rhythms from FP1, FP2, C3, C4, P3, P4, O1 and O2 channels were calculated and combined to form feature vectors for recognizing VRMS. RESULTS: Under the condition of 4-s window size, the average VRMS recognition accuracy of polynomial-SVM for the single subject was 92.85%, and the VRMS recognition accuracy of 18 subjects was about 79.25%. CONCLUSIONS: Compared with other VRMS recognition methods, this method does not only have a higher recognition accuracy to a single subject, but also have better applicability to multiple subjects. Meanwhile, when using the EEG four rhythm energy ratios of FP1, FP2, C3, C4, P3, P4, O1 and O2 channels as feature vectors, the polynomial-SVM achieved better VRMS recognition performance than the k-NN and RBF-SVM.

Explosion characteristics of a pyrolysis biofuel derived from rice husk.

Fast pyrolysis biofuel is considered as one of the promising alternative fuels for future transportation. The authors' research group has improved a pyrolysis biofuel production method for obtaining a biofuel from rice husk. Preliminary research published in Fuel reveals that it has the potential of being used as a gasoline blending component. Before this biofuel can be widely used in real combustors or engines at a large scale, its explosion characteristics should be investigated for the safety consideration during production, transport and storage. This paper quantitatively evaluates explosion pressure, deflagration index, maximum pressure rise rate and combustion duration of this biofuel in the constant volume combustion chamber (CVCC). At the same time, the effects of initial pressure, initial temperature and equivalence ratio on explosion characteristics of this biofuel was also qualitatively analyzed. Linear relationships between explosion pressure, deflagration index, maximum pressure rise rate and combustion duration versus initial pressure and explosion pressure versus initial temperature are given. Results show that explosion pressure is a linear relationship with the initial temperature. However, deflagration index, maximum pressure rise rate and combustion duration are insensitive to the temperature variation.