Multiphysics Modeling for Combustion Instability in Paraffin-Fueled Hybrid Rocket Engines

The use of paraffin-based fuels is a promising approach to a low regression rate in hybrid rocket engines, and the capability to describe and predict combustion instability in the presence of liquefying fuels becomes an enabling step towards the application of hybrid rockets in a wide range of space transportation systems. In this work, a multiphysics model having this purpose is presented and discussed. The model is based on a network of submodels in which chamber gas dynamics is described by a quasi-1D Euler model for reacting flows while thermal diffusion in the grain is described by the 1D heat equation in the radial direction. An artificial neural network is introduced to reduce the computational cost required by the chemical submodel. A sensitivity analysis is performed to identify the key parameters, which have the largest influence on combustion instability and to evaluate the predictive capability of the model despite the uncertainty introduced with the necessary modeling simplifications. Results are presented considering two test cases with different oxidizers: hydrogen peroxide and gaseous oxygen. The procedure shows good agreement with the experimental results available in the literature.