Enhancing UAS safety through building-induced dangerous zones prediction: concept and simulations
Abstract
This study presents a comprehensive approach to operational estimation of the zones of danger for the Unmanned Aerial Systems (UASs) generated at low altitudes in presence of buildings, aimed at ensuring their safer operation. The main tasks are three. The first one is the definition of an inboard measurement methodology appropriate and feasible for UAS that allows Eddy Dissipation Rate (EDR) estimation. An inboard setup with a lightweight and low-cost anemometer operating at a 1 Hz sampling rate, immediately usable on UAS, is proposed. The second one is the definition of empirical equations to estimate the size of dangerous areas for the UAS flights around buildings through numerical simulation. The third one is the validation of the empirical formulas in a real-world case, through the numerical simulation of a group of buildings belonging to a research centre. Results show a good resemblance in the size of the danger zones, highlighting that this multi-faceted approach contributes to enhanced safety protocols for UASs operating in urban environments.
Keyword : Eddy Dissipation Rate, sonic anemometer, UAS, numerical simulation, real-time data, building induced danger zones
How to Cite
Balazova, R., Hlinka, J., Gabrlik, P., Santus, A., & Ferrari, S. (2024). Enhancing UAS safety through building-induced dangerous zones prediction: concept and simulations. Aviation, 28(4), 279–291. https://doi.org/10.3846/aviation.2024.22718
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Chrit, M. (2023). Reconstructing urban wind flows for urban air mobility using reduced-order data assimilation. Theoretical and Applied Mechanics Letters, 13(4), Article 100451. https://doi.org/10.1016/j.taml.2023.100451
Chrit, M., & Majdi, M. (2022). Improving wind speed forecasting for urban air mobility using coupled simulations. Advances in Meteorology. https://doi.org/10.1155/2022/2629432
Diop, M., Dubois, P., Toubin, H., Planckaert, L., Le Roy J.-F., & Garnier, E. (2022). Reconstruction of flow around a high-rise building from wake measurements using Machine Learning techniques. Journal of Wind Engineering and Industrial Aerodynamics, 230, Article 105149. https://doi.org/10.1016/j.jweia.2022.105149
ENVI-met. (n.d.). Homepage. http://www.envi-met.com
Ezaki, T., Fujitsuka, K., Imura, N., & Nishinari, K. (2024). Drone-based vertical delivery system for high-rise buildings: Multiple drones vs. a single elevator. Communications in Transportation Research, 4, Article 100130. https://doi.org/10.1016/j.commtr.2024.100130
Fabbri, K., & Costanzo, V. (2020). Drone-assisted infrared thermography for calibration of outdoor microclimate simulation models. Sustainable Cities and Society, 52, Article 101855. https://doi.org/10.1016/j.scs.2019.101855
Ferrari, S., Rossi, R., & Di Bernardino, A. (2022). A review of laboratory and numerical techniques to simulate turbulent flows. Energies, 15(20), Article 7580. https://doi.org/10.3390/en15207580
Frey, J., Rienecker, H., Schubert, S., Hildebrand, V., & Pfifer, H. (2024). Wind tunnel measurement of the urban wind field for flight path planning of unmanned aerial vehicles. In AIAA SciTech Forum and Exposition. Aerospace Research Central. https://doi.org/10.2514/6.2024-2510
Galway, D., Etele, J., & Fusina, G. (2011). Modeling of urban wind field effects on unmanned rotorcraft flight. Journal of Aircraft, 48(5), 1613–1620. https://doi.org/10.2514/1.C031325
Galway, D., Etele, J., & Fusina, G. (2012). Surveillance applications of unmanned aerial vehicles (UAVs) within urban areas is made difficult by turbulent winds generated by buildings. Journal of Wind Engineering and Industrial Aerodynamics, 103, 73–85. https://doi.org/10.1016/j.jweia.2012.02.010
Giersch, S., Guernaoui, O. E., Raasch, S., Sauer, M., & Palomar, M. (2022). Atmospheric flow simulation strategies to assess turbulent wind conditions for safe drone operations in urban environments. Journal of Wind Engineering and Industrial Aerodynamics, 229, Article 105136. https://doi.org/10.1016/j.jweia.2022.105136
Google. (n.d.). [AdMaS center].
International Civil Aviation Organization. (2001). Meteorological service for international air navigation (Annex 3 to the Convention on International Civil Aviation) (14th ed.). ICAO.
Kim, J., Kim, J.-H., & Sharman, R. D. (2021). Characteristics of energy dissipation rate observed from the high-frequency sonic anemometer at Boseong, South Korea. Atmosphere, 12(7), Article 837. https://doi.org/10.3390/atmos12070837
Kristiansson, M., Andersson Hagiwara, M., Svensson, L., Schierbeck, S., Nord, A., Hollenberg, J., Ringh, M., Nordberg, P., Andersson Segerfelt, P., Jonsson, M., Olsson, J., & Claesson, A. (2024). Drones can be used to provide dispatch centres with on-site photos before arrival of EMS in time critical incidents. Resuscitation, 202, Article 110312. https://doi.org/10.1016/j.resuscitation.2024.110312
Mellor, G. L., & Yamada, T. (1975). A simulation of the Wangara atmospheric boundary layer data. Journal of the Atmospheric Sciences, 32(12), 2309–2329. 2.0.CO;2> https://doi.org/10.1175/1520-0469(1975)032<2309:ASOTWA>2.0.CO;2
Mohamed, A., Marino, M., Watkins, S., Jaworski, J., & Jones, A. (2023). Gusts encountered by flying vehicles in proximity to buildings. Drones, 7(1), Article 22. https://doi.org/10.3390/drones7010022
Palomaki, R. T., Rose, N. T., van den Bossche, M., Sherman, T. J., & De Wekker, S. F. J. (2017). Wind estimation in the lower atmosphere using multirotor aircraft. Journal of Atmospheric and Oceanic Technology, 34, 1183–1191. https://doi.org/10.1175/JTECH-D-16-0177.1
Patrikar, J., Moon, B. G., & Scherer, S. (2020). Wind and the city: Utilizing UAV-based in-situ measurements for estimating urban wind fields. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE. https://doi.org/10.1109/IROS45743.2020.9340812
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Szucs, A. (2013). Wind comfort in a public urban space – case study within Dublin Docklands. Frontiers of Architectural Research, 2(1), 50–66. https://doi.org/10.1016/j.foar.2012.12.002
Wang, Y. Z. D., & Lv, L. (2019). Comparative study of urban residential design and microclimate characteristics based on ENVI-met simulation. Indoor and Built Environment, 28(9), 1200–1216. https://doi.org/10.1177/1420326X19860884
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