Method for Predicting the Impact of Cosmic Rays on Avionics Functionability
Ian Zaczyk
Single Event Effects (SEEs) have been the primary radiation concern for avionics since the late 1980’s when the phenomenon which had previously only been observed in orbiting satellites also began to appear in aircraft electronic systems. The principal SEE affecting avionic devices is the Single Event Upset (SEU) caused when a sole incident particle creates a charge disturbance of sufficient magnitude in a memory cell, flip-flop, latch or register to reverse or flip its currently stored data state. Alternatively, in logic or support circuitry a transient voltage pulse can be nerated that dependent on the right conditions can propagate through the logic of the device and become latched into a memory cell. Transient errors can also be caused by voltage spikes on power supply lines and noise; however these types of disturbances can be suppressed by appropriate shielding and filtering design measures.
The primary sources of radiation are low-energy alpha particles from device and packagingcontaminants, high energy cosmic particles and low energy, (thermal) neutrons. SEEs can be classified into two main categories, soft errors and hard errors. This distinction is made to clarify the difference between soft errors which are transient, non-destructive errors that can be cleared by resetting the device or writing new data to the upset cell and hard errors that are permanent and potentially destructive.
As the reliance on avionics systems within aircraft increases so do concerns regarding the functionability of these systems, particularly for those systems which are considered safety critical. Hence, to take the appropriate mitigating actions and enable decisions to be made at the design stage a method need to be devised that will facilitate the calculation of SEU rates due not only quiescent conditions but also to take into account more exceptional solar influenced events.
In this Lecture the MIRCE Single Event Effects Reliability Prediction Model, developed by Ian Zaczyk, for determination of the avionics systems failure distribution based on accurate predictions of the incident flux environments is presented and discussed.