Numerical Simulation of Spacecraft Charging Attributed to Ionospheric Plasma in Polar and Equatorial Environment

The presence of spacecraft in ionospheric plasma can change plasma properties, vice versa plasma can lead to charge buildup on spacecraft. The level of charging, through electric potential of spacecraft, initially depends on plasma density. However, simulations done on four LEO satellites, i.e. ERS 1, MIDORI, ASCA and FUSE 1, showed that charging level depends on plasma electron temperature rather than plasma density which satisfied the Boltzmann’s relation in the absence of high-energy electrons from aurora. The higher the plasma electron temperature the more spacecraft exposed to negative charging. It is assumed that plasma ions and electrons are collisionless or in Maxwellian distribution. It is found that there is no strong relation between density and charging level. Furthermore, there exists insignificant different of charging between polar and equatorial satellites. It means that the placement of satellite in polar or equatorial region, as long as the presence of auroral electrons is excluded, will suffer similar level of charging which is less than 5V (negative). Since spacecraft are exposed to negative charge, electric field generated by spacecraft potential, together with mesothermal motion effects, deflects ion trajectory into donwstream region leading to ion void region. The ion density is reduced compared to electron density, but there is no significant different of ion void feature between polar and equatorial satellites.and capacity building of beneficiaries.

A Multi-Scale Electromagnetic Particle Code with Adaptive Mesh Refinement and Its Parallelization

AbstractSpace plasma phenomena occur in multi-scale processes from the electron scale to the magnetohydrodynamic scale. In order to investigate such multi-scale phenomena including plasma kinetic effects, we started to develop a new electromagnetic Particle-In-Cell (PIC) code with Adaptive Mesh Refinement (AMR) technique. AMR can realize high-resolution calculation saving computer resources by generating and removing hierarchical cells dynamically. In the parallelization, we adopt domain decomposition method and for good locality preserving and dynamical load balancing, we will use the Morton ordered curve. In the PIC method, particle calculation occupies most of the total calculation time. In our AMR-PIC code, time step intervals are also refined. To realize the load balancing between processes in the domain decomposition scheme, it is the most essential to consider the number of particle calculation loops for each cell among all hierarchical levels as a work weight for each processor. Therefore, we calculate the work weights based on the cost of particle calculation and hierarchical levels of each cell. Then we decompose the domain according to the Morton curve and the work weight, so that each processor has approximately the same amount of work. By performing a simple one-dimensional simulation, we confirmed that the dynamic load balancing is achieved and the computation time is reduced by introducing the dynamic domain decomposition scheme