RESEARCH FIELDEngineering › Aerospace engineeringPhysics › Other
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE31/07/2020 09:00 - Europe/London
LOCATIONFrance › Orléans
TYPE OF CONTRACTTemporary
HOURS PER WEEK35
OFFER STARTING DATE01/09/2020
For a decade, a renewed interest for space propulsion can be witnessed. This surge of activity can be attributed to the emergence of new nations and also private actors as competitors in the market of civil lancers. The objective is to maximize the payloads or lessening the amount of propellants for a given mission. The nozzle as an essential part of a rocket engine can offer a certain margin of progress in this regard by optimizing the flow inside it for different external conditions. In the theoretical approach to this issue, a constantly varying expansion nozzle would be an ideal response to the altitude adaptation issues. However, feasibility of a such nozzle is not possible due to numerous engineering problems. The Dual-Bell Nozzle (DBN), with high theoretical performance gain (∼10%), surfaced in the last two decades is an attractive candidate for industrial application among the altitude compensating nozzle concepts. The dual-bell nozzle (DBN) consists of a base nozzle and a nozzle extension linked by an abrupt change in wall angle. This geometry induce two operating mode. DBN allows the base nozzle section to operate at ground to low altitudes, before the flow attachment to the extension nozzle wall, and high to vacuum operation. DBN provides a simple, high reliability and straightforward optimization without any moving mechanical part which would increases its weight, no need of additional complexities in the system or additional cooling. German DLR evaluated DBN optimization for the current European launchers as Ariane 5, and reported up to 490 kg of payload increase to geostationary orbit (under current price of around 15000$ per payload kilogram adds approximately ∼7M $ per each GTO launch).
However, major DBN drawbacks are inherited from its design which affects base to extension section flow transition, its stability and induced aspiration drag issues. Namely, due to aspiration drag and effects related to boundary layer and expansion adaptation, flow transition occurs before the optimum crossover point, which leads to further thrust loss as compared to an ideal switchover. More, the flow transition (from the sea level to altitude mode) and the re-transition (from the altitude to sea level) take place in a non-axisymmetric way. This induces significant lateral loads which could be dangerous for the launcher’s integrity.
The proposed approach considers the secondary injection downstream of the inflection region. We show very promising results in terms of too low NPR transitioning and re-transitioning which further diminish unwanted unsteady behavior and specific impulse loss during this critical phase. In addition, the proposed injection system can easily be modified to allow thrust vectorization, which would represent a second way of optimization. The present PhD research will be developed by combining experiment and numerical simulation and will follow the steps bellow:
- Study and characterization of natural transition, without manipulation.
- Study and analysis of the effect of the cavity on the natural transition (feeding chamber of the secondary injection)
- Study and characterization of transition control effects (influential parameters, energy cost, limits)
- Study and optimization of thrust vectorization with secondary injection in the second curve.
REQUIRED EDUCATION LEVELEngineering: Master Degree or equivalentPhysics: Master Degree or equivalent
REQUIRED LANGUAGESFRENCH: BasicENGLISH: Good
The candidate must have a master degree in engineering or physics. He must have solid knowledge in fluid mechanics and compressible fluid mechanics. The candidate will shows an interest for the experimentation and/or for the numerical flow simulation. Knowledge would be appreciated in: - Propulsion Physics- Computational fluid dynamics - Labview programming- Python programming - Linux
EURAXESS offer ID: 530571
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