Spatio-temporal Dynamical System Analysis Tools for Very Large Data Sets

Award Information
Department of Defense
Air Force
Award Year:
Phase II
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
Spectral Energies, LLC
5100 Springfield Street, Suite 301, Dayton, OH, 45431-
Hubzone Owned:
Socially and Economically Disadvantaged:
Woman Owned:
Principal Investigator:
Sukesh Roy
CEO&Senior Research Sci
(937) 255-3115
Business Contact:
Sivaram Gogineni
(937) 256-7733
Research Institution:
ABSTRACT: This Phase-II research effort will enable propulsion engineers to design and control next generation propulsion systems (components include: combustors, augmentors, turbines, and compressors etc.) by developing a set of nonlinear analysis tools that can achieve two overarching goals: efficiently analyze large numerical or experimental data sets and provide advanced data mining techniques to more quickly identify relevant dynamical system behavior. This will be accomplished through four key technical objectives: (a) to remove noise from large data sets thereby reducing the quantity of data that needs to be further analyzed by separating the noise from nonlinear dynamics, (b) to remove redundant information from large sets of data to reduce the equivalent of 1 TB of raw data to ~200 GB depending on the flow conditions, (c) to identify dynamically significant information within a very short amount of time to understand the underlying physics of the spatio-temporal dynamical systems, and (d) to develop a set of dynamical invariant tools to compare experimental and numerical data in order to influence the development of next generation war fighters as well as extending the life of existing war fighters. The development of the data analysis tools are required to exploit the current state-of-the-art laser-based measurement systems, which routinely provide 2D temperature and species concentration measurements at a rate of 10 to 50 kHz, as well as to analyze reacting/non-reacting flow data generated by state-of-the-art numerical simulations. The proposed research effort will deliver a user-friendly software module that can be easily integrated to other commercial software systems for analysis of experimental and computational data. BENEFIT: This research effort on the development nonlinear spatio-temporal data analysis tools would allow investigation of turbulent reacting and non-reacting flow phenomena in a real-time basis. This tool set should also allow devising intelligent control strategies for the development of intelligent engines and will have a major impact on understanding of high-speed time-evolving phenomena related to ignition, flame growth, and stability in turbine engine augmentors/afterburners. Hence, this research effort along with methods to analyze high-speed planar and tomographic images will make the concept of real time sensing and control of combustion phenomena a reality. The proposed software system could be easily integrated with any on-board sensing and control system, which would have a significant impact on engine health and stability for the war fighter. Furthermore, in the modeling of non-reacting and reacting flows, it is of great importance to study the interactions among various temporal and spatial scales to understand and predict the complex behavior under turbulent conditions. The objective of this effort is to develop various nonlinear analysis tools for the interpretation of high-bandwidth numerical and experimental data for comparison and validation. The software system should be applicable for any high-bandwidth experimental or numerical data, and as such will have a very broad commercial application covering most of the Universities, Government laboratories, engine companies, automobile companies, etc. Renewed interest in diverse and alternative fuels makes the proposed data analysis tools particularly timely for addressing a number of important research and development needs in high-performance, clean power production from sustainable sources.

* information listed above is at the time of submission.

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