Gas with high pressure is widely used at present as fuel storage mode for different hydrogen vehicles. Differenttypes of materials are used for constructing these hydrogen pressure vessels. An aluminum lined vessel an...Gas with high pressure is widely used at present as fuel storage mode for different hydrogen vehicles. Differenttypes of materials are used for constructing these hydrogen pressure vessels. An aluminum lined vessel and typicallycarbon fiber reinforced plastic (CFRP) materials are commercially used in hydrogen vessels. An aluminumlined vessel is easy to construct and posses high thermal conductivity compared to other commercially availablevessels. However, compared to CFRP lined vessel, it has low strength capacity and safety factors. Therefore,nowadays, CFRP lined vessels are becoming more popular in hydrogen vehicles. Moreover, CFRP lined vesselhas an advantage of light weight. CFRP, although, has many desirable properties in reducing the weight and inincreasing the strength, it is also necessary to keep the material temperature below 85 ℃ for maintaining stringentsafety requirements. While filling process occurs, the temperature can be exceeded due to the compression worksof the gas flow. Therefore, it is very important to optimize the hydrogen filling system to avoid the crossing of thecritical limit of the temperature rise. Computer-aided simulation has been conducted to characterize the hydrogenfilling to optimize the technique. Three types of hydrogen vessels with different volumes have been analyzed foroptimizing the charging characteristics of hydrogen to test vessels. Gas temperatures are measured inside representativevessels in the supply reservoirs (H2 storages) and at the inlet to the test tank during filling.展开更多
Clonal selection feature selection algorithm （CSFS） based on clonal selection algorithm （CSA）, a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-d...Clonal selection feature selection algorithm （CSFS） based on clonal selection algorithm （CSA）, a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm （FCSFS） for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager （PHI） and the airborne visible/infrared imaging spectrometer （AVlRIS）, respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.展开更多
文摘Gas with high pressure is widely used at present as fuel storage mode for different hydrogen vehicles. Differenttypes of materials are used for constructing these hydrogen pressure vessels. An aluminum lined vessel and typicallycarbon fiber reinforced plastic (CFRP) materials are commercially used in hydrogen vessels. An aluminumlined vessel is easy to construct and posses high thermal conductivity compared to other commercially availablevessels. However, compared to CFRP lined vessel, it has low strength capacity and safety factors. Therefore,nowadays, CFRP lined vessels are becoming more popular in hydrogen vehicles. Moreover, CFRP lined vesselhas an advantage of light weight. CFRP, although, has many desirable properties in reducing the weight and inincreasing the strength, it is also necessary to keep the material temperature below 85 ℃ for maintaining stringentsafety requirements. While filling process occurs, the temperature can be exceeded due to the compression worksof the gas flow. Therefore, it is very important to optimize the hydrogen filling system to avoid the crossing of thecritical limit of the temperature rise. Computer-aided simulation has been conducted to characterize the hydrogenfilling to optimize the technique. Three types of hydrogen vessels with different volumes have been analyzed foroptimizing the charging characteristics of hydrogen to test vessels. Gas temperatures are measured inside representativevessels in the supply reservoirs (H2 storages) and at the inlet to the test tank during filling.
基金Supported by the Major State Basic Research Development Program (973 Program) of China (No. 2009CB723905)the National High Technology Research and Development Program (863 Program) of China (Nos.2009AA12Z114, 2007AA12Z148, 2007AA12Z181)+2 种基金the National Natural Sci-ence Foundation of China(Nos. 40771139,40523005, 40721001)the Research Fund for the Doctoral Program of Higher Education of China(No.200804861058)the Foundation of National Laboratory of Pattern Recognition
文摘Clonal selection feature selection algorithm （CSFS） based on clonal selection algorithm （CSA）, a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm （FCSFS） for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager （PHI） and the airborne visible/infrared imaging spectrometer （AVlRIS）, respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.
