Modeling Radiation Risk Assessment and Mitigation for Spacecraft Electronics
Austin, Rebekah Ann
Space-based missions are increasingly having to design and test systems with shorter development times and small budgets and teams. These missions additionally have a higher risk tolerance, leading them to choose commercial parts over radiation-hardened parts in their systems. Additionally, over the last decade, improvements to radiation environment models have enabled the quantification of the uncertainty in the predicted environment, allowing for smaller margins in radiation requirements. In this dissertation, a novel method to calculate the likelihood of radiation-induced destructive faults for silicon carbide power metal-oxide field-effect transistors was developed. The method calculates the probability of failure for destructive single-event burnout and includes environment variability enabled by the PSYCHIC solar heavy-ion environment model. The calculation decouples the part-to-part variability and environment variability. The calculated likelihood can be included with other types of faults and used in system-level probabilistic risk assessment. Additionally, new guidelines for space-radiation risk assessment and risk management within model-based mission assurance are proposed. The guidelines integrate common modeling languages for systems and mission requirements used in model-based systems engineering with information and activities for radiation hardness assurance. A novel fault propagation model is proposed to enable the evaluation of radiation-induced faults and consequences within traditional model-based systems engineering. These guidelines and fault propagation models were implemented on a free-to-use web-based platform supported by NASA’s Office of Safety and Mission Assurance and demonstrated on a CubeSat radiation effects experiment board and for a single-event burnout radiation requirement. These additions to the radiation hardness assurance process enable the inclusion of radiation into model-based mission assurance so that constraint-driven systems can maximize limited resources. By leveraging model-based engineering practices, these constraint-driven teams can use these methods to evaluate radiation risks at the system level and estimate probabilities of failure for destructive effects in emerging technologies.