Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In exist...Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In existing technologies,the efficiency of big data applications(BDAs)in distributed systems hinges on the stable-state and low-latency links between worker nodes.However,LMCNs with high-dynamic nodes and long-distance links can not provide the above conditions,which makes the performance of OBDP hard to be intuitively measured.To bridge this gap,a multidimensional simulation platform is indispensable that can simulate the network environment of LMCNs and put BDAs in it for performance testing.Using STK's APIs and parallel computing framework,we achieve real-time simulation for thousands of satellite nodes,which are mapped as application nodes through software defined network(SDN)and container technologies.We elaborate the architecture and mechanism of the simulation platform,and take the Starlink and Hadoop as realistic examples for simulations.The results indicate that LMCNs have dynamic end-to-end latency which fluctuates periodically with the constellation movement.Compared to ground data center networks(GDCNs),LMCNs deteriorate the computing and storage job throughput,which can be alleviated by the utilization of erasure codes and data flow scheduling of worker nodes.展开更多
In this paper,to study the mechanical responses of a solid propellant subjected to ultrahigh acceleration overload during the gun-launch process,specifically designed projectile flight tests with an onboard measuremen...In this paper,to study the mechanical responses of a solid propellant subjected to ultrahigh acceleration overload during the gun-launch process,specifically designed projectile flight tests with an onboard measurement system were performed.Two projectiles containing dummy HTPB propellant grains were successfully recovered after the flight tests with an ultrahigh acceleration overload value of 8100 g.The onboard-measured time-resolved axial displacement,contact stress and overload values were successfully obtained and analysed.Uniaxial compression tests of the dummy HTPB propellant used in the gunlaunched tests were carried out at low and intermediate strain rates to characterize the propellant's dynamic properties.A linear viscoelastic constitutive model was employed and applied in finite-element simulations of the projectile-launching process.During the launch process,the dummy propellant grain exhibited large deformation due to the high acceleration overload,possibly leading to friction between the motor case and propellant grain.The calculated contact stress showed good agreement with the experimental results,though discrepancies in the overall displacement of the dummy propellant grain were observed.The dynamic mechanical response process of the dummy propellant grain was analysed in detail.The results can be used to estimate the structural integrity of the analysed dummy propellant grain during the gun-launch process.展开更多
相较于传统车载充电系统,集成型车载充电系统(integrated onboard charger system,IOCS)在成本、功率密度等方面具备显著优势。文中基于六相永磁电驱系统设计了一台IOCS,并研究了模型预测电流控制(model predictive current control,MP...相较于传统车载充电系统,集成型车载充电系统(integrated onboard charger system,IOCS)在成本、功率密度等方面具备显著优势。文中基于六相永磁电驱系统设计了一台IOCS,并研究了模型预测电流控制(model predictive current control,MPCC)算法在该系统并网模式下的应用。首先,分析所提IOCS的电路拓扑并建立数学模型,同时介绍传统MPCC的实施流程。然后,针对传统MPCC计算量大、稳态性能差等不足,提出一种基于占空比优化的MPCC(MPCC based on duty cycle optimization,DCO-MPCC)策略。一方面,减少备选电压矢量数量,降低电流预测环节带来的计算负担;另一方面,提出一种占空比优化技术,改善系统稳态性能。最后,通过实验验证了所提算法的有效性与优越性。实验结果表明,DCO-MPCC策略能够显著提升系统稳态性能并减少算法计算量。充电与车网互动(vehicle to grid,V2G)工况下,网侧电流总谐波畸变(total harmonic distortion,THD)分别降低6.18%与5.92%,算法运行时间减少17.54μs。展开更多
基金supported by National Natural Sciences Foundation of China(No.62271165,62027802,62201307)the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515030297)+2 种基金the Shenzhen Science and Technology Program ZDSYS20210623091808025Stable Support Plan Program GXWD20231129102638002the Major Key Project of PCL(No.PCL2024A01)。
文摘Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In existing technologies,the efficiency of big data applications(BDAs)in distributed systems hinges on the stable-state and low-latency links between worker nodes.However,LMCNs with high-dynamic nodes and long-distance links can not provide the above conditions,which makes the performance of OBDP hard to be intuitively measured.To bridge this gap,a multidimensional simulation platform is indispensable that can simulate the network environment of LMCNs and put BDAs in it for performance testing.Using STK's APIs and parallel computing framework,we achieve real-time simulation for thousands of satellite nodes,which are mapped as application nodes through software defined network(SDN)and container technologies.We elaborate the architecture and mechanism of the simulation platform,and take the Starlink and Hadoop as realistic examples for simulations.The results indicate that LMCNs have dynamic end-to-end latency which fluctuates periodically with the constellation movement.Compared to ground data center networks(GDCNs),LMCNs deteriorate the computing and storage job throughput,which can be alleviated by the utilization of erasure codes and data flow scheduling of worker nodes.
文摘In this paper,to study the mechanical responses of a solid propellant subjected to ultrahigh acceleration overload during the gun-launch process,specifically designed projectile flight tests with an onboard measurement system were performed.Two projectiles containing dummy HTPB propellant grains were successfully recovered after the flight tests with an ultrahigh acceleration overload value of 8100 g.The onboard-measured time-resolved axial displacement,contact stress and overload values were successfully obtained and analysed.Uniaxial compression tests of the dummy HTPB propellant used in the gunlaunched tests were carried out at low and intermediate strain rates to characterize the propellant's dynamic properties.A linear viscoelastic constitutive model was employed and applied in finite-element simulations of the projectile-launching process.During the launch process,the dummy propellant grain exhibited large deformation due to the high acceleration overload,possibly leading to friction between the motor case and propellant grain.The calculated contact stress showed good agreement with the experimental results,though discrepancies in the overall displacement of the dummy propellant grain were observed.The dynamic mechanical response process of the dummy propellant grain was analysed in detail.The results can be used to estimate the structural integrity of the analysed dummy propellant grain during the gun-launch process.
文摘相较于传统车载充电系统,集成型车载充电系统(integrated onboard charger system,IOCS)在成本、功率密度等方面具备显著优势。文中基于六相永磁电驱系统设计了一台IOCS,并研究了模型预测电流控制(model predictive current control,MPCC)算法在该系统并网模式下的应用。首先,分析所提IOCS的电路拓扑并建立数学模型,同时介绍传统MPCC的实施流程。然后,针对传统MPCC计算量大、稳态性能差等不足,提出一种基于占空比优化的MPCC(MPCC based on duty cycle optimization,DCO-MPCC)策略。一方面,减少备选电压矢量数量,降低电流预测环节带来的计算负担;另一方面,提出一种占空比优化技术,改善系统稳态性能。最后,通过实验验证了所提算法的有效性与优越性。实验结果表明,DCO-MPCC策略能够显著提升系统稳态性能并减少算法计算量。充电与车网互动(vehicle to grid,V2G)工况下,网侧电流总谐波畸变(total harmonic distortion,THD)分别降低6.18%与5.92%,算法运行时间减少17.54μs。
