Numerical and experimental analysis of fuel regression rate in a lab-scale hybrid rocket engine with swirl injection
Mario Tindaro Migliorino, Marco Fabiani, Christian Paravan, Daniele Bianchi, Francesco Nasuti, Л. Галфетти, Rocco C. Pellegrini, Enrico Cavallini
Abstract
In this work the regression rate performance and flow physics of a lab-scale hybrid rocket engine burning gaseous oxygen and paraffin-based fuels are experimentally and numerically investigated. Regression rates are obtained by thickness-over-time averaging procedures and through a non-intrusive optical method enabling fuel grain port diameter tracking. A numerical rebuilding of the experimental data is performed with axisymmetric Reynolds-averaged Navier-Stokes simulations, using sub-models accounting for the effects of turbulence, chemistry, radiation, and fluid-surface interaction. Simulations are performed with different computational setups, also considering the fuel grain shape variation over time, obtaining a fairly good agreement between the numerical and experimental data. A parametric analysis is also performed to assess the variation of the fuel regression rate with swirl intensity.