Grants and Contributions:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

Gas turbine engines are the de facto power source for aeronautical propulsion, and also play an increasingly large role in electrical power generation. Research and development drivers for gas turbine engines include reducing pollutant emissions (primarily NO x, , CO, and particulates) and increasing sustainability/decreasing climate impact (through use of biofuels), while maintaining safety, robustness, and costs. Two of the major inhibitors to achieving these goals can be summarized as follows:
1) There is a fundamental lack of understanding regarding the potential trajectories for converting reactants to products (i.e. chemical energy conversion pathways) that are enabled by turbulence/combustion interactions at the rather extreme turbulence conditions occurring in gas turbine engines. While traditional models prescribe the same trajectories found in laminar flames, recent experimental and computational evidence disputes this. Such non-laminar trajectories have major implications for how combustors are designed, and open possibilities for novel technologies.
2) All currently known methods for achieving the aforementioned goals increase the probability of various forms of non-stationary combustion dynamics occurring. Phenomena of particular concern are thermoacoustic instabilities, blowout, flashback, and autoignition, any of which can render a system inoperable or cause (potentially catastrophic) damage. It currently is not possible to predict how design or operational changes influence the probability of these phenomena occurring due to gaps in mechanistic understanding and lack of a predictive framework.
The proposed research addresses these issues through two concurrent research themes. Firstly, we will conduct unique experiments that unravel the micro-scale dynamics of turbulent reacting flows at conditions of practical relevance. Specifically, we will use laser measurement techniques to describe the myriad of trajectories through temperature, composition, and reaction rate that fluid can take as it converts from reactants to products.
The second theme takes a larger scale view of combustor dynamics, with the objective of providing a physically-grounded reduced-order method for predicting non-stationary phenomena based on data that is obtainable by engineers working on realistic large-scale systems. To do so, we first will use laser diagnostics to discover and explain the various feedback mechanisms that we hypothesize to drive the different forms of non-stationary behavior. These mechanisms will then be expressed in low-dimensional spaces that best capture the critical perturbation/response behavior of the combustor, but could be accessed in real engine development programs. We then will generate and test various metrics that describe how this behavior changes as the probability of dynamics increases, leading to a predictive framework.