Numerical and experimental analysis of fuel regression rate in a lab-scale hybrid rocket engine with swirl injection

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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.