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GUMP: General Urban Area Microclimate Predictions Tool for Small UAS

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: 80NSSC20C0109
Agency Tracking Number: 193684
Amount: $750,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: A3
Solicitation Number: SBIR_19_P2
Timeline
Solicitation Year: 2019
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-08-12
Award End Date (Contract End Date): 2022-08-11
Small Business Information
15400 Calhoun Drive, Suite 190
Rockville, MD 20855-2814
United States
DUNS: 161911532
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Ankit Tyagi
 (301) 294-4639
 atyagi@i-a-i.com
Business Contact
 Robin Beahm
Phone: (301) 294-5220
Email: rbeahm@i-a-i.com
Research Institution
N/A
Abstract

To successfully integrate small UAS (sUAS) operations in the NAS it is essential to improve the microscale weather prediction. sUAS weigh less than 55 lbs. and 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 manmade 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 sUAS 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 forecast hyperlocal weather is a critical requirement for sUAS operations. During Phase I of the project the team demonstrated the feasibility of the concept by forecasting winds over a nine-block urban area in Manhattan. The technology 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. For the Phase II effort the team proposes to expand the use of GUMP over a larger urban as well as rural area while validating the results with mobile ground-based sensors. When fully functional, GUMP will fill 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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