Reduced-Order Modeling of Unstart in Liquid Fuel Scramjets

Supersonic combustion ramjets, or scramjets, are the most efficient propulsion mode for hypersonic vehicles. However, scramjet propulsion is susceptible to a phenomenon called unstart, wherein the inlet shock system is displaced and the interior flow becomes subsonic, leading to a loss of thrust and impaired vehicle control. Unstart can be triggered by freestream conditions, the inlet/isolator geometry, or internal flow choking, the latter of which remains particularly difficult to simulate and predict due to complex nonlinear interactions between compressible flow, turbulence, fuel injection, and combustion. This represents a critical source of uncertainty and risk for engine design and trajectory planning, which rely on reduced-order models (ROMs) of the flow physics to support rapid evaluation and iteration. Accurate simulations are necessary for verifying these ROMs, and provide crucial insights needed to develop them further. Such simulations require modeling several component physics including turbulence, shock waves, liquid and/or gaseous fuel jets in crossflow, and combustion. Combinations of these give rise to many complex phenomena which are challenging to simulate, such as shock-turbulent-boundary-layer-interaction (STBLI), boundary layer separation, atomization and vaporization of liquid fuels, shock-induced combustion, partially-premixed flames, and flame stabilization and blowout. In this effort, CFD Research and Stanford University will utilize a Large-eddy-simulation solver with the flamelet progress variable method to simulate representative scramjet configurations and characterize the mechanisms driving unstart within them. A novel method for evaluating the flamelet approach and turbulence-chemistry interactions based on the drift term concept will be developed and applied. The transient shock train and transition to full unstart will be analyzed using modal decomposition techniques. Effects of liquid fuel spray, evaporation, and pyrolysis will be investigated with a Lagrangian particle transport approach. The findings will be used to inform improvements to an established physics-based scramjet ROM, which will be evaluated for its accuracy in predicting unstart, as well as to the solver.