Investigating the Tradespace between Increased Automation and Optimal Manning on Aircraft Carrier Decks

With increasing prevalence and capabilities of autonomous systems as part of complex heterogeneous manned-unmanned environments (HMUEs), an important consideration is the impact of the introduction of automation on the optimal assignment of human personnel. The US Navy has implemented optimal staffing techniques before in the 1990's and 2000's with a "minimal staffing" approach. The results were poor, leading to the degradation of Naval preparedness. Clearly, another approach to determining optimal staffing is necessary. To this end, the goal of this research is to develop human performance models for use in determining optimal manning of HMUEs. The human performance models are developed using an agent-based simulation of the aircraft carrier flight deck, a representative safety-critical HMUE. The Personnel Multi-Agent Safety and Control Simulation (PMASCS) simulates and analyzes the effects of introducing generalized maintenance crew skill sets and accelerated failure repair times on the overall performance and safety of the carrier flight deck. A behavioral model of four operator types (ordnance officers, chocks and chains, fueling officers, plane captains, and maintenance operators) is presented here along with an aircraft failure model. The main focus of this work is on the maintenance operators and aircraft failure modeling, since they have a direct impact on total launch time, a primary metric for carrier deck performance. With PMASCS I explore the effects of two variables on total launch time of 22 aircraft: 1) skill level of maintenance operators and 2) aircraft failure repair times while on the catapult (referred to as Phase 4 repair times). It is found that neither introducing a generic skill set to maintenance crews nor introducing a technology to accelerate Phase 4 aircraft repair times improves the average total launch time of 22 aircraft. An optimal manning level of 3 maintenance crews is found under all conditions, the point at which any additional maintenance crews does not reduce the total launch time. An additional discussion is included about how these results change if the operations are relieved of the bottleneck of installing the holdback bar at launch time.

Descending Control of Limb Movements in Drosophila melanogaster

Because the interactions between feedforward influences are inextricably linked during many motor outputs (including but not limited to walking), the contribution of descending inputs to the generation of movements is difficult to study. Here we take advantage of the relatively small number of descending neurons (DNs) in the Drosophila melanogaster model system. We first characterize the number and distribution of the DN populations, then present a novel load free preparation, which enables the study of descending control on limb movements in a context where sensory feedback can be is reduced while leaving the nervous system, musculature, and cuticle of the animal relatively intact. Lastly we use in-vivo whole cell patch clamp electrophysiology to characterize the role of individual DNs in response to specific sensory stimuli and in relationship to movement. We find that there are approximately 1100 DNs in Drosophila that are distributed across six clusters. Input from these DNs is not necessary for coordinated motor activity, which can be generated by the thoracic ganglion, but is necessary for the specific combinations of joint movements typically observed in walking. Lastly, we identify a particular cluster of DNs that are tuned to sensory stimuli and innervate the leg neuromeres. We propose that a multi-layered interaction between these DNs, other DNs, and motor circuits in the thoracic ganglia enable the diverse but well-coordinated range of motor outputs an animal might exhibit.