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Robust-Mode Analysis, Reduced-Order Modeling, and Intelligent Control Strategies for Reacting and Non-Reacting Flows

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9300-18-C-2501
Agency Tracking Number: F12B-T15-0060a
Amount: $749,977.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: AF12-BT15
Solicitation Number: 2012.0
Solicitation Year: 2012
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-05-22
Award End Date (Contract End Date): 2020-05-22
Small Business Information
5100 Springfield Street
Dayton, OH 45431
United States
DUNS: 782766831
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Dr. Sukesh Roy
 (937) 902-6546
Business Contact
 Dr. Sivaram Gogineni
Phone: (937) 256-7733
Research Institution
 Purdue University
 Mike Springer
585 Purdue Mall
West Lafayette, IN 47907
United States

 (765) 496-3707
 Domestic Nonprofit Research Organization

This Phase-II STTR research effort is designed to forward the engineering investigation of the dynamics and control of turbulent combustion in high-pressure combustion systems by developing a set of game-changing nonlinear analysis tools that can significantly improve the post-processing speed and intelligent data mining of large numerical or experimental data sets. Moreover, a system based on nonlinear dynamical phase-space analysis (such as Chaos Theory) will be explored for reduced order modeling (ROM), devising control strategies, and providing quantitative information for system identification and comparison. The preliminary results of some of these analysis approaches were demonstrated during the Phase-I research effort on experimental data provided by Edwards AFB and numerical data related to the CVRC combustor. The final deliverable of this research effort will be user-friendly software incorporating various mathematical tools for analyzing experimental and numerical data. It is expected to have a range of applications, including establishing quantitative differences between experimental flows and validating models of various experimental systems. The software will contain a user-friendly interface that can be used to pre-process the data, construct reduced order models, test and refine various control strategies, and compute the dynamical invariants for the dynamics. The approaches proposed in this research effort will

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

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