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Reduced Order Modeling (ROM) for UUV/USV Environmental Awareness -- 19-013

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0349
Agency Tracking Number: N19A-022-0190
Amount: $139,978.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N19A-T022
Solicitation Number: 19.A
Solicitation Year: 2019
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-06-03
Award End Date (Contract End Date): 2019-12-09
Small Business Information
1818 Library Street Suite 600
Reston, VA 20190
United States
DUNS: 107939233
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Dr. Dennis Bazow Dr. Dennis Bazow
 Analyst I
 (703) 326-2905
Business Contact
 Seth Blackwell
Phone: (703) 326-2907
Research Institution
 University of Miami
 Ms Aida Diaz Ms Aida Diaz
1320 S Dixie Hwy
Coral Gables, FL 33146
United States

 (305) 421-4089
 Nonprofit College or University

In Phase I, Metron and the University of Miami (UM) propose to develop a theoretic reduction of dynamics framework applicable to the prediction of oceanographic fields in geophysical fluid dynamic models for use onboard unmanned platforms. Our approach leverages, extends and combines modern advances in the renormalization group and Bayesian probability combined with fluid dynamics modeling and forecasting. We will adopt a mathematical procedure called the renormalization group (RG) method from theoretical physics to systematically reduce the dynamics to a simpler representation with a fewer number of degrees of freedom confined to a lower dimensional space. The renormalization group plays a prominent role in modern theoretical physics, especially in dealing with problems that have multiple time or length scales, and is uniquely suited for the reduction of dynamic oceanographic fields. It has applications in many areas such as the reduction of transport equations to fluid dynamics and the analysis of turbulence. The RG based reduced order modeling (ROM) framework is extensible to forecasting the evolution of dynamic fields which is critical for making optimal control decisions.

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

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