摘要
针对现有尘埃动力学仿真多使用连续充电策略,忽略电荷“量子化”性质对于纳米尺寸尘埃颗粒的影响这一问题,以起源于木卫一的木星尘埃流现象为研究对象,在动力学建模过程中考虑随机充电过程,以更合理地模拟纳米尺寸尘埃颗粒表面电量和轨迹的演化过程。随机充电模型仿真结果表明,只有8~200 nm尺寸范围内的尘埃颗粒可以以6~240 km/s的速度从木星磁层中逃逸。与连续充电模型的仿真结果进行对比,发现对于携带少量电荷的极小尺寸的尘埃颗粒而言,在其动力学模拟过程中考虑充电机制的“量子化”和“随机性”特点是必要的。最后通过简化模型针对尘埃流颗粒的尺寸范围进行了估计,理论结果和随机充电模型仿真结果基本相符。木星系统奇特的等离子体环境和磁场环境共同塑造了尘埃流现象,而随机充电过程则进一步使得尘埃颗粒的轨迹演化变得复杂多样。
Regarding existing dust dynamics simulations,a continuous charging model was commonly employed,neglecting the influence of the quantized nature of electric charges on nanoscale dust grains.In this study,focusing on the dust stream phenomenon originating from Io,a stochastic charging process was considered in the dynamic modeling to more accurately simulate the nanoscale dust grains'evolution of the electrical charge and trajectory.The simulation results obtained from the stochastic charging model indicate that only dust grains within the size range of 8~200 nm are capable of escaping from the Jovian magnetosphere at speeds of 6~240 km/s.Subsequently,upon comparing the simulation results of the continuous charging model,it was determined that accounting for the"quantization"and"randomness"of the charging mechanism is essential in the dynamic simulation process of tiny dust particles carrying a small charge.Finally,a simplified model was employed to estimate the size range of dust stream particles,and the theoretical results generally agree with the simulation results obtained from the stochastic charging model.The peculiar plasma and magnetic field environments of Jupiter system collectively shape the dust stream phenomenon,while the stochastic charging process further contributes to the diverse evolution of dust particle trajectories.
作者
梁有鹏
刘晓东
LIANG Youpeng;LIU Xiaodong(School of Aeronautics and Astronautics,Shenzhen Campus of Sun Yat-sen University,Shenzhen 518107,China;Shenzhen Key Laboratory of Intelligent Microsatellite Constellation,Shenzhen Campus of Sun Yat-sen University,Shenzhen 518107,China)
出处
《空间科学与试验学报》
CSCD
2024年第1期54-62,共9页
Journal of Space Science and Experiment
基金
国家自然科学基金资助项目(12002397,12311530055,62388101)
国家重点研发计划课题(2020YFC2201202,2020YFC2201101)
深圳市科技计划资助项目(ZDSYS20210623091808026)。
