A conceptual Object-Oriented Bayesian Network (OOBN) for modeling aircraft carrier-based UAS safety risk

This paper illustrates the conceptual development of a demonstration Object-Oriented Bayesian Network (OOBN) to integrate the hazards associated with an experimental Unmanned Aircraft System (UAS) planned for deployment from an aircraft carrier. The final Air/Ship Integration (A/SI) demonstration model is characterized by a top-level Bayesian network model with nine sub-nets comprising 70 causal factors with 15 mitigations. With the creation of a probabilistic model, inferences about changes to the states of the causal factors given the presence or absence of controls or mitigations can be ascertained. These inferences build on qualitative reasoning and enable an analyst to identify the most prominent causal factor groupings leading to a prioritization of the most influential causal factors. Mitigation effects can be systematically studied and assessed. The A/SI OOBN demonstration model illustrates the construction of an integrative safety risk model that may be used to compute a higher-order system mishap probability for an experimental UAS that interacts with ship operations in a highly severe, dynamic sea environment. In addition to computing mishap probabilities, the Bayesian approach may also be used to support control contingency management for possible mitigation implementation.