Skip to Main Content
Ground-based electron charging tests are commonly performed as part of satellite design qualification. The objective of the test is to determine the severity of the resulting electrostatic discharges (ESD) and, via subsequent analysis, determine the hazard they pose to the health and function of the satellite. ESD tests generate large data sets because of the substantial and random variation in ESD amplitudes. The variability is readily apparent in time series scatter plots. The average amplitude, the range of amplitudes (standard deviation), and a worst case event in a set of data are immediately seen. If a failure threshold is known, the margin between that threshold and both the average and worst case events can be shown. Common practice is to compare either the worst case observed event or a 3-sigma upper limit to the failure threshold when assessing the risk of ESD-induced failure. Several samples of ESD test data are reviewed, and the cumulative probability distributions are shown to follow a power law relationship. Applying a Gaussian distribution to the data implies failure is nearly impossible, whereas the power law shows failure is certain because the power law has fatter tails in the extreme event end of the distribution. The consequences of fat tails for ESD risk assessment are discussed.