SUMMARY

Even the simplest swirling jet flows possess an astonishing degree of complexity. This complexity is a two-edged sword, presenting both a unique opportunity to advance the science of fluid mechanics as well as a major barrier for a variety of engineering applications. In particular, swirling jet technologies have proven crucial for enabling the increased efficiencies and drastically-reduced emissions seen in modern combustion systems. However, the enhanced mixing and flame stability characteristics offered by swirling flow configurations are constrained by a relatively limited understanding of their dynamics, which continues to press the power and propulsion industry against the limits of reliable performance. This research is comprised of two major, complimentary thrusts centered on the dynamics of swirling jets and flames. The first focuses on rigorously characterizing the behavior of laminar swirling jets and flames from a dynamical systems perspective using bifurcation analysis. These results offer several new insights into the physics of swirling jets, such as demonstrating bistability between competing low pressure regions and characterizing the bifurcation and nonlinear evolution of a variety of coherent limit-cycle structures from an initially steady state. The effect of combustion on these processes is also considered. The second portion of the work addresses the more practical need for reliable reduced-order models of turbulent swirling jets and flames. A linear hydrodynamic-acoustic response framework is developed in order to predict the coherent response of a swirling reacting jet to external acoustics. This model is validated against measurements from acoustically-forced experiments, showing that many important aspects of the forced response can be characterized on the basis of very affordable computations. Using experimental data, the work also analyzes the relationship between large-scale coherent vortical structures and incoherent turbulent fluctuations, with a focus on assessing the ability of turbulence models to capture these interactions.