Magnin, Michael — National Aeronautics and Space Administration SBIR Phase I: H6

Description

<p>With future missions of increasing complexity, duration, distance, and uncertainty, there has been a growing need for methods and tools that can permit the effective formation of early stage conceptual designs that are not only cost-effective, but also productive and resilient to failures. Current approaches are mostly tailored to evaluating independent systems but do not necessarily scale well to problems requiring a system-of-systems approach. Furthermore, current approaches are not well suited to evaluating metrics such as system resiliency. Due to extended mission duration and distance, a new paradigm is entering the space mission design area which involves systems that change over time (either by changing the system capabilities, repairing the system, or resupplying the system). This adds complexity to the mission, and uncertainty regarding the system performance.</p><p style="margin-left:0in; margin-right:0in">This proposal addresses these issues with the following innovations:</p><ol><li>Development of a method and a set of tools that evaluate and optimize of system resilience during its conceptual design stage</li><li>Introduction of metrics that evaluate system performance as a function of other metrics such as the system cost, resilience, reliability and safety</li><li>Development of a scenario-based optimization to propagate uncertainty associated with the planned operation of the system</li> </ol><p style="margin-left:0in; margin-right:0in">The significance of the innovations is that the proposed methods and tools will:</p><ol><li>Permit the simultaneous optimization of a system-level design, a system-of-system-level design, and the resilience of a system-of-systems</li><li>Permit the evaluation of the impact of component-level reliabilities and subsystem designs on system-level resilience and performance</li><li>Allow for the propagation of uncertainty related to the planned operation of the system to be integrated into the resilience-based design optimization and evaluated concurrently with design and reliability uncertainties</li> </ol>