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ENCIT 2020
18th Brazilian Congress of Thermal Sciences and Engineering
Performance Prediction Software for Hybrid Rocket Motors
Submission Author:
Renato Filho , SP
Co-Authors:
Renato Filho, Maurício Sá Gontijo
Presenter: Renato Filho
doi://10.26678/ABCM.ENCIT2020.CIT20-0355
Abstract
Hybrid rocket motors (HRMs) have great potential on becoming a widely used propulsion system. The nitrous oxide is one of the most used oxidizers in this technology, because it enables the use of a simple feeding system, due to the self-pressurizing properties of N2O. Due to its two-phase characteristics, a correct and accurate modelling of its physics is necessary to the correct design of the motor. In addition, the grain regression, or burnback, may get time to model and, in general, it is applicable only to the target geometry. With this in consideration, a methodology for performance calculation of hybrid rocket motors is described in this work, providing a computational tool to make it accessible for propulsion engineers. In addition, it is also possible to consider a pressurized system. The software developed, Hybrid Propulsion Modeling and Design (HPMD), couples some models that describes the behavior of two key hybrid propulsion characteristics: i) the self-pressurizing feed system, and ii) the regression of the fuel grain, with a blowdown and a burnback model, respectively. In order to predict the overall performance of the motor the software is also coupled with the Chemical Equilibrium with Applications (CEA) program, to make precise internal ballistics calculation. Also, tools are provided to aid the user to design the motor, such as a propellant analysis, an injector head design and a nozzle design tool. The results from the HPMD, the trend over time of performance parameters, were compared with experimental curves from a hybrid tested motor. It has been proved to be a powerful, complete, and reliable tool for the design of hybrid rocket motors.
Keywords
Hybrid, Motor Performance, Blowdown, Burnback, Regression
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