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Realistic wind data are essential in developing, testing, and ensuring the safety of unmanned aerial systems in operation. Alternatives to Dryden and von Kármán turbulence models are required, aimed explicitly at urban air spaces to generate turbulent wind data. We present a novel method to generate realistic wind data for the safe operation of small unmanned aerial vehicles in urban spaces. We propose a non-intrusive reduced order modeling approach to replicate realistic wind data and predict wind fields. The method uses a well-established large-eddy simulation model, the parallelized large eddy simulation model, to generate high-fidelity data. To create a reduced-order model, we utilize proper orthogonal decomposition to extract modes from the three-dimensional space and use specialized recurrent neural networks and long-term short memory for stepping in time. This paper combines the traditional approach of using computational fluid dynamic simulations to generate wind data with deep learning and reduced-order modeling techniques to devise a methodology for a non-intrusive data-based model for wind field prediction. A simplistic model of an isolated urban subspace with a single building setup in neutral atmospheric conditions is considered a test case for the demonstration of the method.
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Semi-analytical range and endurance computation of battery-powered multi-copter unmanned aerial systems under steady wind conditions
The range and endurance of an unmanned aerial system operating nominally in an outdoor environment depends upon the available power and environmental factors like the magnitude and direction of the prevailing wind. This paper focuses on the development of semi-analytical approaches to computing the range and endurance of battery-powered multi-copter unmanned aerial system under varying wind conditions. The analytically derived range is verified against a comprehensive unmanned aerial system simulation which includes experimentally validated elements such as the propulsion system and electric power consumption modules. It is shown that the analytical approach yields the range maps in close agreement with the simulation results.
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- Award ID(s):
- 1724248
- PAR ID:
- 10545159
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
- Volume:
- 233
- Issue:
- 14
- ISSN:
- 0954-4100
- Format(s):
- Medium: X Size: p. 5282-5294
- Size(s):
- p. 5282-5294
- Sponsoring Org:
- National Science Foundation
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