Inverse Approach to Spacecraft Charging Simulations

Spacecraft charging is a major topic of space-weather research since charging can lead to spacecraft anomalies, ranging from inconsequential to catastrophic. Spacecraft surface charging calculations use sophisticated numerical codes and are typically performed 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 or highly inaccurate when some of the critical input parameters are either unknown or have large uncertainties. For instance, the Van Allen Probes spacecraft, also known as RBSP, is an example of a modern spacecraft with state-of-the-art measurements. Predicting the RBSP 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 how materials age in space due to their interaction with the environment is not well understood. To mitigate these limitations, we developed an inverse approach to use available spacecraft-charging data to infer some of the unknown properties of the space environment around the spacecraft and spacecraft material degradation. Our inversion is composed of an ensemble of constrained optimization solutions that provide an estimate of the parameter values of interest. Our approach is validated with an analytical model of spacecraft charging, based on the orbital-motion-limited theory, together with a quasi-Newton optimization method. Our results show convergence and the ability to estimate the correct parameters in synthetic observation experiments.