GUMP: General Urban Area Microclimate Predictions Tool for Small UAS

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: 80NSSC19C0445
Agency Tracking Number: 193684
Amount: $125,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A3
Solicitation Number: SBIR_19_P1
Solicitation Year: 2019
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-08-19
Award End Date (Contract End Date): 2020-02-18
Small Business Information
15400 Calhoun Drive, Suite 190, Rockville, MD, 20855-2814
DUNS: 161911532
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Ankit Tyagi
 (301) 294-4639
Business Contact
 Robin Beahm
Phone: (301) 294-5220
Research Institution
There are a number challenges to small UAS operations in the NAS. One of the most critical of these is access to microscale, hyperlocal weather estimates and predictions.Small UAS weigh less than 55 lbs have the risk of losing control in presence of light winds and gusts. The risk is amplified in urban areas due to presence of tall building and other man made objects. The phenomenon of urban canyon can cause high winds between building that are beyond the capabilities of current meso scale weather prediction models. High demand operations such as package delivery involves the UAS to take off from fulfilment center, travel to the destination and land where the customers are and takeoff for the return journey. Therefore, the ability to predict hyperlocal weather is a critical requirement for UAS in the NAS operations. The team propose to develop GUMP, a weather service that combines the coarse estimates of mesoscale prediction from NOAA weather products with high fidelity but localized ground station data using machine learning and computation fluid dynamics simulations. The innovative approach is scalable and transferrable to urban or rural areas. The computational workload is minimized by building on weather forecast publically available. GUMP fills a critical gap in weather prediction technology that will be beneficial for NASA researchers and industry UAS operators.

* Information listed above is at the time of submission. *

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