Work Description

Title: A Simulated Wind-field Dataset for Testing Energy Efficient Path-Planning Algorithms for UAVs in Urban Environment Open Access Deposited

http://creativecommons.org/publicdomain/zero/1.0/
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Methodology
  • We simulate a wind field in a region near the city of Boston at coordinates 42°15'17.9"N and 71°08'27.7"W. The simulation of the flow physics in this region exhibits significant variation in local velocity direction and magnitude, and thus can potentially serve as a useful test case for UAM. The CAD footprints for the region are made available by the Boston Planning and Development Agency. The extracted geometry of the region chosen is rendered using commercially available Autocad package. Two dimensional numerical simulations are carried out for the generated using open source SU2 suite. Compressible steady Reynold’s Averaged Navier-Stoke’s (RANS) equations are solved for the flow domain with initial boundary conditions chosen to suitably replicate the actual field variables. An Implicit Euler scheme is set to meet results with residual of 10^-6, and a Lower-Upper Symmetric-Gauss-Seidel (LU-SGS) method is used to increase the convergence speed of the code. The boundary conditions, no slip wall and farfield, are fixed based on this history of velocity profile local to the area obtained from National Weather Services. Simulations are performed at varying Mach numbers and far field wind angles.
Description
  • Studying the effect of wind on urban air mobility typically requires comprehensive fluid dynamics simulations in a realistic urban geometry. Motivated to enable wide-spread autonomous drone activity in urban centers, such studies have indeed been considered by several authors in the recent literature. However, the accessibility of these approaches to those with less fluid dynamics experience and/or without access to purpose built simulation tools has limited validation and application of the resulting path planning strategies.

  • The .dat files contain the flow variables for each of the 402240 points sampled from the region under study. For flow visualization purposes, the .dat files are readable using Tecplot Software.
Creator
Depositor
  • deepikab@umich.edu
Contact information
Discipline
Funding agency
  • Other Funding Agency
Other Funding agency
  • DARPA program on Physics of AI, and in part by the Computational Mathematics Program of the AFOSR (P.M. Fariba Fahroo)
Keyword
Citations to related material
Resource type
Curation notes
  • The following files were added to this data set at the request of its creators on November 27, 2019: case_m0.02200.dat, case_m0.02300.dat, case_m0.02400.dat, case_m0.02500.dat, case_m0.02600.dat, case_m0.02700.dat, case_m0.02800.dat, case_m0.02900.dat, case_m0.03000.dat.

  • The read me file was edited to update information about the funder of the research and the methodology at the request of the creators of this data set on November 27, 2019.
Last modified
  • 12/02/2019
Published
  • 11/19/2019
Language
DOI
License
To Cite this Work:
Baskar, D., Gorodetsky, A. (2019). A Simulated Wind-field Dataset for Testing Energy Efficient Path-Planning Algorithms for UAVs in Urban Environment [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/pdcv-0x63

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