Inverse Problem Approach to Spacecraft Charging Simulations

Abstract:

Spacecraft charging is a major application of space-weather research since charging can lead to spacecraft anomalies, which can range from inconsequential to catastrophic. Spacecraft surface charging calculations use sophisticated numerical codes and are typically conducted with a direct (forward) approach: the local properties of the space environment, the spacecraft geometry and the spacecraft material properties are the input, while the electric field on and around the spacecraft and the corresponding plasma particle distributions are the output. This approach can be limited when some of the critical input parameters are either unknown or have large uncertainties. For instance, the Van Allen Probes (VAP) spacecraft is an example of a modern spacecraft with state-of-the-art measurements. Predicting the VAP spacecraft potential requires knowledge of the cold and warm plasma populations which dominate surface charging. However, the cold plasma properties (particularly temperature) are not well characterized. In addition, the material properties are known from measurements in laboratory 'clean' conditions but there are uncertainties associated with how materials age in space due to their interaction with the environment.

To mitigate these limitations, we developed an inverse approach to use available spacecraft-charging data to infer some of the missing properties of the space environment around the spacecraft and material degradation. Our approach was initially developed with an analytical model of spacecraft charging, based on the orbital-motion-limited theory, together with a quasi-Newton optimization method. We will present results that show convergence and the ability to estimate the correct parameters in synthetic observation experiments. Other approaches are also being tested to minimize the number of iterations required by the inverse procedure to converge. The optimization machinery has then been ported to the Curvilinear Particle-in-cell (CPIC) code for parameter estimation using a first-principle model of spacecraft charging and we will discuss the challenges of coupling the inverse approach with PIC simulations. Finally, some preliminary application of the inverse approach to VAP data will also be presented.