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Regression rate estimation for standard-flow hybrid rocket engines
Authors:David R Greatrix
Institution:1. Federal Science Center Scientific Research Institute for System Analysis of the Russian Academy of Sciences, 36-1 Nakhimovskiy pr, Moscow 117218, Russia;2. Moscow M.V. Lomonosov State University, Leninskie Gory 1, Moscow 119992, Russia;1. Onera – The French Aerospace Lab, F-31410, Mauzac, France;2. Onera – The French Aerospace Lab, F-31055, Toulouse, France;1. Università di Napoli “Federico II”, Dipartimento di Ingegneria Industriale, P.le Tecchio 80, 80125 Napoli, Italy;2. Seconda Università di Napoli, Dipartimento di Ingegneria Industriale e dell''Informazione, via Roma 29, 81031 Aversa (CE), Italy;1. School of Astronautics, Beihang University, 100191, China;2. Key Laboratory of Spacecraft Design Optimization & Dynamic Simulation Technologies, Ministry of Education, China;3. Beijing Institute of Electronic System Engineering, The R & D Center of the Second Academy, CASIC, Beijing, 100854, China
Abstract:The present effort is towards predicting with some accuracy hybrid rocket engine fuel regression rates under standard flow conditions. A convective heat feedback modelling approach is applied in tying the mass-flux-dependent heat flux directed into the regressing fuel surface, to the subsequent solid fuel grain regression rate. Factors such as transpiration, hydraulic port diameter, and effective fuel surface roughness are incorporated into the phenomenological surface regression rate model. A number of comparisons between the model's predicted results and corresponding experimental data are made, in illustrating the efficacy of the present approach for a classical head-end-injection engine. Where substantial differences between theory and experiment exist, this might be due to one of several identifiable factors related to non-standard flow, such as the presence of radiant heating, swirl or flow impingement in or at the boundaries of the experimental core flow.
Keywords:
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