As the basis of location-based services(LBS),positioning is one of the most essential parts in intelligent transportation systems(ITS).Although global positioning system(GPS)has been widely used in vehicle positioning...As the basis of location-based services(LBS),positioning is one of the most essential parts in intelligent transportation systems(ITS).Although global positioning system(GPS)has been widely used in vehicle positioning,it can not achieve lane level positioning accuracy.Motivated by the mature ranging technologies such as radar and ultra-wideband(UWB),several cooperative positioning(CP)methods have been proposed to enhance the accuracy and robustness of GPS.In this paper,we proposed a twostage CP algorithm that combines multidimensional scaling(MDS)and Procrustes analysis for vehicles with GPS information.Specifically,the optimized MDS based on the scaling by majorizing a complicated function(SMACOF)algorithm is first proposed to get the relative coordinates of vehicles which can tackle measurements of different error distributions,then Procrustes analysis is carried out to transform the relative coordinates of vehicles to their absolute coordinates based on GPS information.All the computations are performed at the mobile edge computing node(MECN)for the request of ultra-reliable and low latency communications(URLLC).Simulation results validate that the proposed algorithm can greatly improve the positioning accuracy and robustness for vehicles.展开更多
The catalyst layer （CL） of proton exchange mem-brane fuel cell （PEMFC） involves various particles and pores in meso-scale, which has an important effect on the mass, charge （proton and electron） and heat transpo...The catalyst layer （CL） of proton exchange mem-brane fuel cell （PEMFC） involves various particles and pores in meso-scale, which has an important effect on the mass, charge （proton and electron） and heat transport coupled with the electrochemical reactions. The coarse-grained molecular dynamics （CG-MD） method is employed as a meso-scale structure reconstruction technique to mimic the self-organization phenomena in the fabrication steps of a CL. The meso-scale structure obtained at the equilibrium state is further analyzed by molecular dynamic （MD） software to provide the necessary microscopic parameters for understanding of multi-scale and-physics processes in CLs. The primary pore size distribution （PSD） and active platinum （Pt） surface areas are also calculated and then compared with the experiments. In addition, we also highlight the implementation method to combine microscopic elementary kinetic reaction schemes with the CG-MD approaches to provide insight into the reactions in CLs. The concepts from CG modeling with particle hydrodynamics （SPH） and the problems on coupling of SPH with finite element modeling （FEM） methods are further outlined and discussed to understand the effects of the meso-scale transport phenomena in fuel cells.展开更多
基金This work was supported in part by the National Key Research and Development Program of China(2019YFB1600100)in part by the Foundation of Shaanxi Key Laboratory of Integrated and Intelligent Navigation under Grant SKLIIN-20190103.
文摘As the basis of location-based services(LBS),positioning is one of the most essential parts in intelligent transportation systems(ITS).Although global positioning system(GPS)has been widely used in vehicle positioning,it can not achieve lane level positioning accuracy.Motivated by the mature ranging technologies such as radar and ultra-wideband(UWB),several cooperative positioning(CP)methods have been proposed to enhance the accuracy and robustness of GPS.In this paper,we proposed a twostage CP algorithm that combines multidimensional scaling(MDS)and Procrustes analysis for vehicles with GPS information.Specifically,the optimized MDS based on the scaling by majorizing a complicated function(SMACOF)algorithm is first proposed to get the relative coordinates of vehicles which can tackle measurements of different error distributions,then Procrustes analysis is carried out to transform the relative coordinates of vehicles to their absolute coordinates based on GPS information.All the computations are performed at the mobile edge computing node(MECN)for the request of ultra-reliable and low latency communications(URLLC).Simulation results validate that the proposed algorithm can greatly improve the positioning accuracy and robustness for vehicles.
文摘The catalyst layer （CL） of proton exchange mem-brane fuel cell （PEMFC） involves various particles and pores in meso-scale, which has an important effect on the mass, charge （proton and electron） and heat transport coupled with the electrochemical reactions. The coarse-grained molecular dynamics （CG-MD） method is employed as a meso-scale structure reconstruction technique to mimic the self-organization phenomena in the fabrication steps of a CL. The meso-scale structure obtained at the equilibrium state is further analyzed by molecular dynamic （MD） software to provide the necessary microscopic parameters for understanding of multi-scale and-physics processes in CLs. The primary pore size distribution （PSD） and active platinum （Pt） surface areas are also calculated and then compared with the experiments. In addition, we also highlight the implementation method to combine microscopic elementary kinetic reaction schemes with the CG-MD approaches to provide insight into the reactions in CLs. The concepts from CG modeling with particle hydrodynamics （SPH） and the problems on coupling of SPH with finite element modeling （FEM） methods are further outlined and discussed to understand the effects of the meso-scale transport phenomena in fuel cells.
