Structural characterization and regression rate of solidified ethanol fuels for hybrid rocket applications

Abstract

The success of hybrid rockets in future military and commercial applications will depend on their ability to utilize fuels that are not only easy-to-process, safe, and environmental-friendly but also meet operational demands of high regression rate and efficient combustion. In this study, the eco-friendly ethanol fuel is solidified using Methylcellulose (MC) and Hydroxypropyl Methylcellulose (HPMC) as the organic gellants and de-ionized water as the solvent and proposed for usage as a fuel for hybrid rocket applications. The gellant concentration is varied in the range of 10 – 14 % while the nano aluminum concentration is varied in the range 2–6 wt% for HPMC and 2–4 wt% for MC samples. Through FTIR, TMDSC, and TGA the solidification mechanism of this tri-component system is proposed. It is found that two types of non-covalent interactions lead to 3D-network formation between gellant molecules and ethanol–water mixture, and hence, solidification. One, the hydrophobic association between alkyl chains of the gellant, and two, the intra and the inter-molecular hydrogen bonding of hydroxyl groups in gellant molecules. Subsequently, the regression rate of solid fuels is investigated as a function of the oxidizer flux ranging from 0.97 – 11.7 kg/m2-s in an opposed flow burner facility (OFB). Over the range of oxidizer fluxes, the regression rate of solid ethanol fuels is higher than the conventional fuels such as HTPB and DCPD and comparable to that of paraffin wax. The high regression rate is attributed to their low melting points and enthalpy of melting, strongly shear thinning behavior, and the occurrence of vapor jetting, which in addition to fuel gasification aids in advective transport of unreacted fuel vapors to the flame zone. Finally, the effect of oxidizer flux and nanoparticle concentration on the regression rate is analyzed. Irrespective of the fuel, the regression rate increases monotonically with the oxidizer flux whose degree depends on the flow regime i.e., laminar versus turbulent

being higher for the latter. Further, in the laminar regime, there is no effect of increasing nanoparticle loading on the regression rate while in the turbulent flow regime the regression rate increases rapidly with increasing concentration. © 2022 Elsevier Ltd