Fundamental Insights into Combustion Instability Predictions in Aerospace Propulsion

Cheng Huang, Purdue University

Abstract

Integrated multi-fidelity modeling has been performed for combustion instability in aerospace propulsion, which includes two levels of analysis: first, computational fluid dynamics (CFD) using hybrid RANS/LES simulations for underlying physics investigations (high-fidelity modeling); second, modal decomposition techniques for diagnostics (analysis & validation); third, development of flame response model using model reduction techniques for practical design applications (low-order model). For the high-fidelity modeling, the relevant CFD code development work is moving towards combustion instability prediction for liquid propulsion system. A laboratory-scale single-element lean direct injection (LDI) gas turbine combustor is used for configuration that produces self-excited combustion instability. The model gas turbine combustor is featured with an air inlet section, air plenum, swirler-venturi-injector assembly, combustion chamber, and exit nozzle. The combustor uses liquid fuel (Jet-A/FT-SPK) and heated air up to 800K. Combustion dynamics investigations are performed with the same geometry and operating conditions concurrently between the experiment and computation at both high (&phis;=0.6) and low (&phis;=0.36) equivalence ratios. The simulation is able to reach reasonable agreement with experiment measurements in terms of the pressure signal. Computational analyses are also performed using an acoustically-open geometry to investigate the characteristic hydrodynamics in the combustor with both constant and perturbed inlet mass flow rates. Two hydrodynamic modes are identified by using Dynamic Mode Decomposition (DMD) analysis: Vortex Breakdown Bubble (VBB) and swirling modes. Following that, the closed geometry simulation results are analyzed in three steps. In step one, a detailed cycle analysis shows two physically important couplings in the combustor: first, the acoustic compression enhances the spray drop breakup and vaporization, and generates more gaseous fuel for reaction; second, the acoustic compression couples with the unsteady hydrodynamics found in the open-geometry simulation, enhances the fuel/air mixing, and triggers a large amount of heat addition. In step two, a modal analysis using DMD extracts the dynamic features of important modes in the combustor, and identifies the presence of Precessing Vortex Core (PVC) mode and its nonlinear interactions with acoustic modes. Moreover, the DMD analysis helps to establish the couplings between the hydrodynamics and acoustics in terms of frequencies. In step 3, Rayleigh index analysis provides a quantitative assessment of acoustics/combustion couplings and identifies local regions for instability driving/damping. Two modal decomposition techniques, Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD), are assessed in terms of their capabilities in extracting important information from the original simulation dataset and in validating the computational results using the experiment measurement. A POD analysis provides a series of modes with decreasing energy content and it offers an efficient and optimized way to represent a large dataset. The frequency-based DMD technique provides modes that correspond to all single frequencies. For the low-order modeling, fundamental aspects are examined to study necessary conditions, criteria and approaches to develop a reduced-order model (ROM) that is able to represent generic combustion/flame responses, which then can be used in an engineering level tool to provide efficient predictions of combustion instability for practical design applications. Explorations are focused on model reduction techniques by using the so-called POD/Galerkin method. The method uses the numerical solutions of the model equations as the database for building a set of POD eigen-bases. Specifically, the numerical solutions are calculated by perturbing quantities of interest such as the inlet conditions. The POD-derived eigen-bases are, in turn, used in conjunction with a Galerkin procedure to reduce the governing partial differential equation to an ordinary differential equation, which constitutes the ROM. Once the ROM is established, it can then be used as a lower-order test-bed to predict detailed results within certain parametric ranges at a fraction of the cost of solving the full governing equations. A detailed assessment is performed on the method in two parts. In part one, a one-dimensional scalar reaction-advection model equation is used for fundamental investigations, which include verification of the POD eigen-basis calculation and of the ROM development procedure. Moreover, certain criteria during ROM development are established: 1. a necessary number of POD modes that should be included to guarantee a stable ROM; 2. the need for the numerical discretization scheme to be consistent between the original CFD and the developed ROM. Furthermore, the predictive capabilities of the resulting ROM are evaluated to test its limits and to validate the values of applying broadband forcing in improving the ROM performance. In part two, the exploration is extended to a vector system of equations. Using the one-dimensional Euler equation is used as a model equation. A numerical stability issue is identified during the ROM development, the cause of which is further studied and attributed to the normalization methods implemented to generate coupled POD eigen-bases for vector variables. (Abstract shortened by UMI.)

Degree

Ph.D.

Advisors

Wang, Purdue University.

Subject Area

Aerospace engineering|Mechanical engineering

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