ases of microprocessors, ASICs, linear circuits, ADCs, detectors, and other components which exhibit sensitivity to soft errors from protons. Typically, requirement documents call for a level of performance, and it is the job of the box manufacturer to allocate error rates due to various expected sources. For orbits encountering the inner belts, protons often dominate average soft error rates in technologies sensitive to their effects. Where error rates are required to stay below some allowed maximum, the peak trapped proton flux and peak solar particle event fluxes represent the greatest challenges. For orbits outside of the proton belts, such as geostationary at 36,000 km, average proton arrival rates may be extremely low, but proton upset sensitivity can be a design driver with the infrequent solar particle event in mind. 2.3.4 Margin: Design margins arise from a variety of concerns and are expressed in a variety of ways, with some of these concerns specific to protons. Where large uncertainties exist either in the ability to predict the environment with high confidence or in the ability to predict circuit response, margin is applied to mitigate risk. In fact, the degree of margin is often scaled according to the criticality of the function being performed with the idea that survival is most important and some mission objectives are more important than others [e.g., Gate-96]. One of the sources of uncertainty is in the environment models. As an example, for trapped protons, the 23 year old AP-8 model has served to establish average and peak proton fluxes as well as proton dose for the radiation belts. The uncertainty associated with that model is stated to be a factor of two for long term orbit averages and higher for short duration periods (e.g., less than 1 year) [Sawy-76]. Therefore, it is appropriate to either double the predicted trapped particle environment or impose margin on the ability of the system to perform in the predicted environment. System designers frequently employ either approach. New inform