Pediatric practitioners in the tristate area reported that children/families sought care for an array of mental health-related concerns. Generalists in the areas affected and those who identified gaps in knowledge or skills in responding to the psychological effects of community disasters should be targeted for additional education.
With the rising popularity of small unmanned aircraft systems (sUAS), more commonly known as drones, in both the public and private sectors, there is a growing need to organize and study aerial traffic flow. To improve the safety and efficiency of sUAS traffic, a study of sUAS behavior under heavy wind conditions was undertaken. A new model for sense-and-avoid behavior was developed, taking into account the effects of three different types of winds: headwinds, tailwinds, and consistent winds. To confirm the accuracy of the model, its microscopic form was then transformed into a macroscopic model to describe the group behavior of a platoon of vehicles. A MATLAB simulation was programmed to model the flow of a large group of sUAS affected by each different type of wind. Macroscopic data from the three trials were then plotted, and the plots were examined to analyze the nature of the relationships between density, flow, and speed values. Ultimately, it was found that the models produce feasible results and can be used to approach the behavior of externally forced sUAS flow. Various practical applications for these new models were proposed, and suggestions for further research were identified.
Small unmanned aircraft systems (sUAS), better known as “drones,” have been drastically increasing in ownership and popularity during recent times. While this technology was once restricted to military and hobbyist use, numerous public and private-sector groups have proposed new uses, such as package delivery and firefighting. As the number of sUAS in operation increases, the methods currently utilized to manage sUAS traffic flow are expected to become inadequate; thus, it is necessary to develop an alternate system of sUAS traffic management. This paper proposes a computerized simulation methodology to quantitatively evaluate air traffic management methods based on safety, efficiency, and computational intensity. This methodology is then used to test the current organization method against free competition for available airspace and a freeway-style method of traffic organization known as an “air highway.” It was ultimately found that these alternate methods of organization are less foolproof than the current method with regards to safety, but are significantly more practical to implement due to reduced computational intensity; additionally, these methods are sometimes capable of reducing travel time.
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