In this study, series of novel composite phase change materials(PCMs) were prepared through vacuum impregnation by using meso-porous carbon as a supporting matrix and n-octadcane as PCMs.The meso-porous carbon materia...In this study, series of novel composite phase change materials(PCMs) were prepared through vacuum impregnation by using meso-porous carbon as a supporting matrix and n-octadcane as PCMs.The meso-porous carbon material was prepared through one-pot co-assembly method, using resorcinol and formaldehyde as carbon precursor, tetraethoxysilane as silica sources and triblock copolymer F127 as a template. And the phase behaviors of n-octadcane confined in the nano-porous structure of the meso-porous carbon were further investigated. Fourier transform-infrared spectroscopy spectra show that n-octadecane was effectively encapsulated in the porous structure of mesoporous carbon and the composite PCMs were successfully prepared. Differential scanning calorimetry results confirm that the composite PCMs possess a good phase change behavior, fast thermal-response rate and excellent thermal cycling stability. In addition, the composite PCMs possess expected heat storage and heat release properties. All these results demonstrate that the composite PCMs possess good comprehensive property so that they can be used widely in energy storage systems.展开更多
This study aims to solve path planning of ntelligent vehicles in self driving In this study,an improved path planning method com-bining constraints of the environment and vehicle is proposed.The algorithm designs a re...This study aims to solve path planning of ntelligent vehicles in self driving In this study,an improved path planning method com-bining constraints of the environment and vehicle is proposed.The algorithm designs a reasonable path cost function,then uses a heuristic guided search strategy to improve the speed and quality of path planning,and finally generates smooth and continuous cur-vature paths based on the path post-processing method focusing on the requirements of path smoothness.A simulation test shows that compared with the basic rapidly-exploring random tree(RRT),RRT-Connect and RRT*algorithms,the path length of the proposed algorithm can be reduced by 19.7%,29.3%and 1%respectively,and the maximum planned path curvature of the proposed algorithm is 0.0796 mr1 and 0.1512 mi respectively.under the condition of a small amount of planning time.The algorithm can plan the more suitable driving path for intelligent vehicles in a complex environment.展开更多
基金financially supported by the National Natural Science Foundation of China (Grant Nos. 51102230, 51462006, 51361005, 51863005, U1501242, 51371060 and 51671062)the Guangxi Natural Science Foundation (Nos. 2014GXNSFAA118401, 2013GXNSFBA019244, 2014GXNSFAA118319 and 2014GXNAFDA118005)+2 种基金Guangxi Key Laboratory of Information Materials (Nos. 161002-Z, 171027-Z and 161002-K)Guangxi Scientific Technology Team (No. 2012GXNSFGA06002, AA17202030)the Program for Postgraduate Joint Training Base of GUET-CJYRE (No. 20160513-14-Z)
文摘In this study, series of novel composite phase change materials(PCMs) were prepared through vacuum impregnation by using meso-porous carbon as a supporting matrix and n-octadcane as PCMs.The meso-porous carbon material was prepared through one-pot co-assembly method, using resorcinol and formaldehyde as carbon precursor, tetraethoxysilane as silica sources and triblock copolymer F127 as a template. And the phase behaviors of n-octadcane confined in the nano-porous structure of the meso-porous carbon were further investigated. Fourier transform-infrared spectroscopy spectra show that n-octadecane was effectively encapsulated in the porous structure of mesoporous carbon and the composite PCMs were successfully prepared. Differential scanning calorimetry results confirm that the composite PCMs possess a good phase change behavior, fast thermal-response rate and excellent thermal cycling stability. In addition, the composite PCMs possess expected heat storage and heat release properties. All these results demonstrate that the composite PCMs possess good comprehensive property so that they can be used widely in energy storage systems.
基金Supported by Guangdong Natural Science Foundation(Grant No.2015A030310411)Guangdong University Char acteristic Innovation(Grant No.2018KQNCX207)+1 种基金Shaoguan science and technology plan(Grant No.2018sn043)Shaoguan university scientific research(Grant No.sz2018KJ06).
文摘This study aims to solve path planning of ntelligent vehicles in self driving In this study,an improved path planning method com-bining constraints of the environment and vehicle is proposed.The algorithm designs a reasonable path cost function,then uses a heuristic guided search strategy to improve the speed and quality of path planning,and finally generates smooth and continuous cur-vature paths based on the path post-processing method focusing on the requirements of path smoothness.A simulation test shows that compared with the basic rapidly-exploring random tree(RRT),RRT-Connect and RRT*algorithms,the path length of the proposed algorithm can be reduced by 19.7%,29.3%and 1%respectively,and the maximum planned path curvature of the proposed algorithm is 0.0796 mr1 and 0.1512 mi respectively.under the condition of a small amount of planning time.The algorithm can plan the more suitable driving path for intelligent vehicles in a complex environment.
