Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CN...Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CNG)/diesel dual fuel engine (DFE) was one of the best solutions for the above problems at present. In order to study and improve the emission performance of CNG/diesel DFE, an emission model for DFE based on radial basis function (RBF) neural network was developed which was a black-box input-output training data model not require priori knowledge. The RBF centers and the connected weights could be selected automatically according to the distribution of the training data in input-output space and the given approximating error. Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. The developed emissions model based on the RBF neural network could be used to successfully predict and optimize the emissions performance of DFE. And the effect of the DFE main performance parameters, such as rotation speed, load, pilot quantity and injection timing, were also predicted by means of this model. In resumé, an emission prediction model for CNG/diesel DFE based on RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value, although it still has some limitations, because of its high dependence on the quantity of the experimental sample data.展开更多
This study was to investigate the effect of ozone （ O3 ） inactivation on Giardia in water by the fluorescence staining method. In order to elucidate the dominant mechanisms of inactivation, cell surface or inner cel...This study was to investigate the effect of ozone （ O3 ） inactivation on Giardia in water by the fluorescence staining method. In order to elucidate the dominant mechanisms of inactivation, cell surface or inner cell components damage were comparatively examined by scanning dectron microscopy （SEM）. Results suggested that O3 had a stronger effect on inactivating capability. Firstly, when the concentration of O3 was above 2.0 mg/L and the contact time was up to 5 min, it showed a significant inactivating effect. Secondly, the effect of turbidity on inactivation was also found to be significant in synthetic water; when turbidity increased, the inactivating effect decreased. Thirdly, the inactivating rates were improved with a temperature increase from 5 to 25℃, but decreased when the temperature were out of this range. The inactivating capability of O3 was stronger under acidic conditions than alkalic conditions. Lastly, when the concentration of organic matter in the reactive system was increased, probably due to the competition between G/ard/a and organics on O3, the inactivating rate was decreased; in addition, the cellular morphology of Giardia varied with different contact times. At contact time of 30 s, cells were rotundity and sphericity; at 60 s they became folded, underwent emboly, and burst; and at 240 s, the cell membrane of Giardia shrinked and collapsed completely.展开更多
文摘Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CNG)/diesel dual fuel engine (DFE) was one of the best solutions for the above problems at present. In order to study and improve the emission performance of CNG/diesel DFE, an emission model for DFE based on radial basis function (RBF) neural network was developed which was a black-box input-output training data model not require priori knowledge. The RBF centers and the connected weights could be selected automatically according to the distribution of the training data in input-output space and the given approximating error. Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. The developed emissions model based on the RBF neural network could be used to successfully predict and optimize the emissions performance of DFE. And the effect of the DFE main performance parameters, such as rotation speed, load, pilot quantity and injection timing, were also predicted by means of this model. In resumé, an emission prediction model for CNG/diesel DFE based on RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value, although it still has some limitations, because of its high dependence on the quantity of the experimental sample data.
基金National High Technology Research and Development Program ("863"Program) of China(No.2006AAZ309)Science and Technology Project of Guangdong Province,China(No.2011B030800018)Natural Science Foundation of Guangdong Province,China(No.2012040007855)
文摘This study was to investigate the effect of ozone （ O3 ） inactivation on Giardia in water by the fluorescence staining method. In order to elucidate the dominant mechanisms of inactivation, cell surface or inner cell components damage were comparatively examined by scanning dectron microscopy （SEM）. Results suggested that O3 had a stronger effect on inactivating capability. Firstly, when the concentration of O3 was above 2.0 mg/L and the contact time was up to 5 min, it showed a significant inactivating effect. Secondly, the effect of turbidity on inactivation was also found to be significant in synthetic water; when turbidity increased, the inactivating effect decreased. Thirdly, the inactivating rates were improved with a temperature increase from 5 to 25℃, but decreased when the temperature were out of this range. The inactivating capability of O3 was stronger under acidic conditions than alkalic conditions. Lastly, when the concentration of organic matter in the reactive system was increased, probably due to the competition between G/ard/a and organics on O3, the inactivating rate was decreased; in addition, the cellular morphology of Giardia varied with different contact times. At contact time of 30 s, cells were rotundity and sphericity; at 60 s they became folded, underwent emboly, and burst; and at 240 s, the cell membrane of Giardia shrinked and collapsed completely.
