We propose to create model-based simulation and analysis techniques for risk management throughout the system life cycle. Rather than using traditional approaches based on failure events in static engineering designs, we will treat a system as a dynamic process that is continually adapting to achieve its ends and to react to changes in itself and its environment. The original design must not only enforce appropriate constraints on behavior to ensure safe operation, but the system must continue to operate safely as changes occur. To achieve this goal, the process leading up to an accident (loss event) can be described in terms of an adaptive feedback function that fails to maintain safety as performance changes over time to meet a complex set of goals and values. Using this definition of risk management, we will determine how to extend our commercial system engineering toolset to include model-based simulation and analysis of risk throughout the system life cycle, including complex human decision-making, software errors, system accidents (versus component failure accidents), and organizational risk factors. POTENTIAL COMMERCIAL APPLICATIONS The results of this SBIR research will be potentially applicable to every NASA project where significant losses can result from the operation or lack of operation of the system. It should be particularly important in systems with significant software and human automation interaction components and in large projects where management decisions about risk are critical and need to be supported.
