Abstract
There is a major push in safety-critical systems to consider system risk early in the design process in order to avoid costly redesign later on. However, existing techniques, which may be labor-intensive and be subject to many sources of uncertainty, rely on failure mode and failure rate data, which can only be estimated in the early design phase. This paper proposes a network-based technique for assessing the consequential importance of a particular component to enable designers to consider hazards in the design of the system architecture without the use of estimated failure rates. Structural consequence analysis represents connectivity between components with a network and provides an explicit representation of risk prevention and mitigation techniques, such as redundancy. The network is augmented with a measure of the consequence of the failure of the “end” components, or sinks, which can be backpropagated through the network to compute the consequence associated with the failure of all components. Based on this consequence, designers can consider mitigation strategies, such as redundancy or increased component reliability. The approach is demonstrated in the design of an electric system to control an aileron of an unmanned aircraft system (UAS). It is found that structural consequence analysis can identify potentially important components without failure rate data, allowing designers to proactively design for risk earlier in the design process.
A simple extrapolated predictor for overcoming the starting and tracking issues in the arc-length method for nonlinear structural mechanics
