New Paradigms in High Pressure Combustion Dynamics Prediction and Control

ABSTRACT:In this project we seek to transition major recent developments in the mathematics of model reduction to industrial grade computing applications in liquid rocket combustion instability. From the mathematical side, we are interested in unsteady nonlinear dynamical systems which exhibit limit-cycle behavior and large oscillations and potentially discontinuous solutions. From the applications perspective, we are interested in a practical simulation capability for large multi-injector liquid hydrocarbon fueled rocket engines such as the Hydrocarbon Boost demonstration (HCB) engine that are of contemporary interest. Combustion instability is a key concern in new rocket development efforts. Predictive computer modeling can serve a vital role in risk reduction at a relatively low cost. Present day simulation tools, while trending towards a comprehensive self-consistent physical model set and becoming increasingly better verified and validated, still place enormous demands on computer resources needed for realistic simulations.A software suite named HDrbm developed here will address black-box capabilities in model reduction for nonlinear multiphysical applications. HyPerComp will team with the Scientific Computing and Imaging Institute at the University of Utah in developing mathematical methods and software system in this project. The team will also benefit from consulting support from key researchers in applied mathematics and turbulent combustion modeling.BENEFIT:This work has direct relevance to major ongoing liquid rocket engine programs where stability studies are overwhelmed by the computational problem size, and can benefit from improvements in methodology. The models and methodologies developed here are also directly relevant to solid propellant rockets and gas turbine combustors. The general scope of the methods developed here is indeed rather vast. The reduced basis method has applications in numerous markets: automotive, nuclear, image processing, and atmospheric science to name a few. Successful phase-II research automatically enables control algorithms, optimization and uncertainty based predictions for combustion dynamics.