REGRESSION RATE MODELS VERSUS EXPERIMENTAL RESULTS FOR HYBRID ROCKET ENGINES BASED ON H2O2 AND HTPB/AL

Abstract

The regression rate of the solid fuel is a major factor in hybrid rocket engine (HRE) design. It is very important to have a reliably-predicted regression rate to design an application-related hybrid rocket engine which will meet the required thrust profile. Many different models have been proposed with very different levels of complexity and are related to a broad number of HRE propellant types and combustion mechanisms. Often they have a lack of generality concerning the HRE working regime in terms of pressure, oxidizer mass flow and scaling. The regression rate predictions by 3 major models of Marxman, Smoot and Price and Chiaverini are calculated for the test setup and compared to experimental results of the HRE demonstrator, developed within the DLR research program AHRES. Emphasis was placed on the model predictions for the regression rate depending on the grain length and not for different working regimes. The HRE demonstrator of the AHRES program is equipped with a fuel grain in telescope geometry. The solid fuel consists of HTPB with aluminum particles. Hydrogen peroxide with a concentration of 87.5% is used as oxidizer. The oxidizer mass flow rate was 0.9 kg/s at a chamber pressure of 4.5 MPa. The regression rate models of Marxman and Chiaverini showed good agreement with the test run, the model of Smoot and Price predicted regression rate over 50% too low.