Correlation of Hybrid Rocket Propellant Regression Measurements with Enthalpy-Balance Model Predictions

Abstract

An enthalpy-balance fuel-grain regression model is presented. The regression model, based on the longitudinally averaged fuel recession rates, is shown to accurately predict the chamber pressure, thrust and specific impulse performance of small and medium scale hybrid rocket motors. The key to the model predictions is the longitudinal enthalpy balance between the fuel grain heat of ablation and the convective heat transfer from the flame zone to the model surface. Convective heat transfer is related to the surface skin friction using the Reynolds analogy for turbulent flow. Simple flat plate models are used to predict the longitudinally averaged skin friction coefficient. Chemical properties of the combustion products were evaluated using the NASA Computer Equilibrium with Applications (CEA) Combustion code. Model predictions for a nitrous oxide (N 2 O) and hydroxylterminated poly butadiene (HTPB) motor are compared to data from a small-scale test firing with a 10.2-cm diameter motor. Suggestions for model improvements are offered.