Project Number: 094
Currently, unmanned aircraft systems (UAS) noise is most often assessed on an operator/vehicle specific basis using a collection of generalized methodologies based on a combination of vehicle specific acoustical data as well as trajectory and operations data provided by potential UAS operators. While this approach is sufficient for assessing the potential noise implications of initial small-scale, operator specific unmanned aircraft (UA) operations, improved methodologies and tools are needed to assess the wider noise implications of UA operations as they expand to include larger operating areas, multiple operators, and vehicles. The goal of this project is to develop one or multiple methodologies or tools to support the development of probabilistic distributions of UAS operations, based on the expected stochastic nature of their operations. These methods will then be used to determine the statistical likelihood of where operations may occur, accompanied, or integrated with a probabilistic determination of the resulting UA noise exposure. This will support computation of noise resulting from the operation of UAS and other upcoming vehicle concepts. Methodology development will leverage emerging statistical and computational technologies to achieve fast and efficient modeling of a potentially large number of vehicles and operations with uncertain locations and trajectories.
This research effort will produce a methodology that can evaluate the noise exposure, and associated uncertainty in the noise exposure, that could result from the introduction of large numbers of UAS vehicles into commercial and private use. This will aid in the rapid computation of uncertainty distributions in noise levels. The resulting probabilistic noise exposure maps and visualizations will provide decision-makers insight on likelihood of where the noise would be distributed or concentrated. This method could also help identify innovative operational concepts to promote sustainable growth of UAS operations by minimizing noise generation over sensitive areas.
Last updated 7/10/2023