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Ph.D. Thesis Defense by
(Advisors: Prof. Wenting Sun and Prof. Vigor Yang)
Friday, 5th May 2017 @ 1:00 p.m.
Guggenheim Building Room 442
Abstract:
The development of combustion energy-conversion systems requires accurate simulation tools, such as Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES), for ignition, combustion instability, lean blowout, and emissions. Because of high computational cost, DNS and LES typically employ either a flamelet model with detailed chemistry or an over-simplified finite rate chemistry. Both approaches, however, are of limited accuracy and may reduce the quality of prediction. In this dissertation, we establish a new numerical framework for DNS and LES of turbulent combustion, employing correlated dynamic adaptive chemistry (CoDAC), correlated evaluation of transport properties (CoTran), and a point-implicit stiff ODE solver (ODEPIM). CoDAC utilizes a path flux analysis (PFA) method to reduce the large chemical kinetics to a smaller size for each location and time step. CoTran uses a similar correlation method to accelerate the evaluation of mixture-averaged diffusion (MAD) coefficients.
The framework is first tested on a canonical turbulent premixed flame. Compared to conventional DNS, the total computation time of the new framework is 20 times faster, chemical kinetics is 46 times faster, and transport is 72 times faster, while maintains high accuracy and good parallel scalability. Based on above DNS framework, an efficient finite-rate chemistry (FRC) - LES formulation is developed. Compared to conventional FRC-LES, this new version provides a speed-up of 8.6 times for chemistry, and 6.4 times for total computation. Both new FRC-LES and flamelet/progress-variable (FPV)-LES are conducted for a piloted partially premixed methane/air flame. Although the two approaches predict similar time-averaged flame and statistics; instantaneously, FPV-LES predicts significantly smaller regions with high temperature. Near the stoichiometric region, with respect to experimental data, FPV-LES over-predicts the radical generation, but under-predicts the CO generation and heat release, which explains its under-prediction of temperature. In contrast, on the fuel rich side, CO is no more a bottleneck, and FPV-LES predicts higher temperature. Comparing to experimental data, FRC-LES provides better predictions for temperature and species.
Most chemical kinetics models offer similar predictions in 0D/1D simulations of laminar combustion. Is it appropriate to extend this observation to 3D turbulent combustions? In order to answer this question, GRI-Mech 3.0 and an 11-species syngas model are compared by performing 3D finite-rate DNS of a turbulent non-premixed syngas flame. Significant quantitative discrepancies indicate high sensitivity to the chemical kinetics model. The 11-species model predicts a lower radicals-to-products conversion rate, causing statistically more local extinction and less re-ignition. This sensitivity is magnified relative to a 1D steady laminar simulation by the effects of unsteadiness and turbulence, with the deviations in species concentrations, temperature, and reaction rates forming a nonlinear positive feedback loop. The differences between the two models are primarily due to: (a) the larger number of species in GRI-Mech 3.0; and (b) the differences in reaction rate coefficients for the same reactions in the two models. Both (a) and (b) are sensitive to unsteadiness and other turbulence effects, but (b) is dominant and more sensitive.
Committee:
Dr. Wenting Sun, AE
Dr. Vigor Yang, AE
Dr. Suresh Menon, AE
Dr. Yiguang Ju, Princeton MAE
Dr. Yingjie Liu, MATH
