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International Journal of Energetic Materials and Chemical Propulsion
ESCI SJR: 0.28 SNIP: 0.421 CiteScore™: 0.9

ISSN Imprimir: 2150-766X
ISSN En Línea: 2150-7678

International Journal of Energetic Materials and Chemical Propulsion

DOI: 10.1615/IntJEnergeticMaterialsChemProp.2016013641
pages 249-274

NUMERICAL MODELING OF COMBUSTION PROCESSES IN HYBRID ROCKET ENGINES

Alessandro Mazzetti
Blue Think S.P.A., 20124 Milano, Italy
Paolo Barbante
Politecnico di Milano, Department of Mathematics, 20133 Milano, Italy

SINOPSIS

Nowadays, numerical simulations of combustion processes in hybrid rockets are generally considered as a qualitative tool used mainly to describe the flow field inside the rocket engine. A research effort is of major importance in order to change this trend. It can be done by obtaining results that are quantitatively accurate, to be used as a support for experimental research, reducing costs, and increasing efficiency in the development of better fuel formulations. The importance of such an effort relies on the fact that hybrid rockets are one of the most promising technologies in the aerospace propulsion field, with applications in hypersonic atmospheric flight, launch vehicles' upper stages, and space tourism, which is seen as a prelude for an economically feasible mass access to space. This is possible because of hybrid propulsion's low cost, intrinsic safety, and operational flexibility with potentially high performances. This research contribution aims to develop an accurate combustion model for traditional rubber-based hybrid rocket fuels (hydroxyl-terminated polybutadiene). Results of the simulations are presented as temperature distribution, axial velocity, and the products' mass fractions. A discussion about local and average fuel regression rates is presented, with particular attention to the effects on both the local and average regression rate, due to an increase in oxidizer mass flux and in pressure. Results of the present work suggest that an increase in oxidizer mass flux gives an increase in the average regression rate, while an increase in pressure gives a reduction in the average regression rate.


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