MAE Seminar: Data-enabled Design for Combustion Dynamics in Propulsion Engines

Abstract: This lecture will address a multifidelity modeling strategy to facilitate data-enabled design of combustion devices for propulsion engines. As a specific example, the issue of combustion dynamics (unsteady flow motions in combustion chambers) will be discussed. 

An interdisciplinary research program is underway, focused on the development of an efficient and robust capability to understand, analyze and predict combustion dynamics in contemporary and future propulsion systems. This effort involves work in supercritical combustion, combustion instability, reduced-basis modeling (emulation), statistics, uncertainty quantification and machine learning. Recent breakthroughs in modeling and data analytics techniques have been utilized to substantially improve the modeling capabilities at all levels. New techniques address issues specific to physics extraction and design evaluation of complex systems, such as rocket and gas turbine engines. This research will enable effective and efficient (practical time-scale) surveys of all known parameters, including design attributes and operating conditions, and their effects on system stability behavior.

The integrated approach described here starts with large eddy simulation (LES)-based high-fidelity modeling and simulations of combustion dynamics in engines. Reduced-basis models and emulation then leverage the database established by the LES for physics-based data assimilation. Stochastic-based extraction of physics from complex flowfields provides faithful and interpretable representations of the underlying mechanisms.  Feature extraction techniques are incorporated into a spatio-temporal surrogate model built on machine-learning techniques such as Gaussian process (GP) regression. Combined with statistical methodologies and control theories, these techniques allow for an efficient survey of flow evolution and combustion dynamics, with special attention to the identification of combustion response and gas-dynamic driving mechanisms. Data-driven quantification of the transfer function between the identified mechanisms is achieved. Finally, a system-level model is developed for effective and efficient assessment of the combustion stability behaviors of a practical system with complex geometry over a broad range of operating conditions.

Bio: Vigor Yang is the William R. T. Oakes Professor and Chair in the School of Aerospace Engineering at the Georgia Institute of Technology. He has published 10 comprehensive volumes and numerous technical papers on combustion, propulsion and energetics.  He was the recipient of  the Air-Breathing Propulsion Award (2005), the Pendray Aerospace Literature Award (2008), the Propellants and Combustion Award (2009), and the von Karman Lectureship in Astronautics Award (2016) from the American Institute of Aeronautics and Astronautics (AIAA); the Worcester Reed Warner Medal (2014) from the American Society of Mechanical Engineers (ASME); and the Lifetime Achievement Award (2014) from the Joint Army, Navy, NASA and Air Force (JANNAF) Interagency Propulsion Committee. Yang was the editor-in-chief of the AIAA Journal of Propulsion and Power (2001-2009) and the JANNAF Journal of Propulsion and Energetics (2009-2012). He is currently a co-editor of the Aerospace Book Series of the Cambridge University Press (2010-present). A member of the U.S. National Academy of Engineering and an Academician of Academia Sinica, Yang is a fellow of the AIAA, ASME and Royal Aeronautic Society (RAeS).