LOX/methane and LOX/kerosene high thrust engine trade-off

Pempie, Pascal; Fröhlich, Thomas; Vermin, Hilda

doi:10.2514/6.2001-3542

Cited by 24 publications

(4 citation statements)

References 8 publications

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“…These soot depositions can decrease the effective nozzle area up to 20 % [2], thus reducing the turbopump performance. Furthermore, soot depositions are a main shortcoming for reusable engines due to the unpredictable impacts for engine re-start [44].…”

Section: Simulation Environment and Rl Implementationmentioning

confidence: 99%

A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines

Waxenegger-Wilfing¹,

Dresia²,

Deeken³

et al. 2021

IEEE Trans. Aerosp. Electron. Syst.

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Nowadays, liquid rocket engines use closed-loop control at most near steady operating conditions. The control of the transient phases is traditionally performed in open-loop due to highly nonlinear system dynamics. This situation is unsatisfactory, in particular for reusable engines. The open-loop control system cannot provide optimal engine performance due to external disturbances or the degeneration of engine components over time. In this paper, we study a deep reinforcement learning approach for optimal control of a generic gas-generator engine's continuous start-up phase. It is shown that the learned policy can reach different steady-state operating points and convincingly adapt to changing system parameters. Compared to carefully tuned open-loop sequences and PID controllers, the deep reinforcement learning controller achieves the highest performance. In addition, it requires only minimal computational effort to calculate the control action, which is a big advantage over approaches that require online optimization, such as model predictive control.

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Section: Simulation Environment and Rl Implementationmentioning

confidence: 99%

A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines

Waxenegger-Wilfing¹,

Dresia²,

Deeken³

et al. 2021

IEEE Trans. Aerosp. Electron. Syst.

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show abstract

Section: Test Casementioning

confidence: 99%

A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines

Waxenegger-Wilfing,

Dresia,

Deeken

et al. 2020

Preprint

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Nowadays, liquid rocket engines use closedloop control at most near steady operating conditions. The control of the transient phases is traditionally performed in open-loop due to highly nonlinear system dynamics. This situation is unsatisfactory, in particular for reusable engines. The open-loop control system cannot provide optimal engine performance due to external disturbances or the degeneration of engine components over time. In this paper, we study a deep reinforcement learning approach for optimal control of a generic gas-generator engine's continuous start-up phase. It is shown that the learned policy can reach different steady-state operating points and convincingly adapt to changing system parameters. A quantitative comparison with carefully tuned open-loop sequences and PID controllers is included. The deep reinforcement learning controller achieves the highest performance and requires only minimal computational effort to calculate the control action, which is a big advantage over approaches that require online optimization, such as model predictive control.

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“…22 Institutions in the USA, Russia, China, and Europe have already done some work on the research of LOX/methane LRE, including its thermodynamic cycle, flame stabilization, comparison of kerosene and methane as rocket fuels, and so on. [23][24][25] In addition to the balancing characteristics in thermodynamic properties and specific impulse, researches indicate three more positive properties of methane as an aerospace fuel. First, methane is a ''clean'' fuel which means that it has less soot deposition as its coking point is roughly twice as high as kerosene.…”

Section: Analysis Of Lox/methane Liquid-rocket Engine (Lre)mentioning

confidence: 99%

Conceptual study of a dual-rocket-based-combined-cycle powered two-stage-to-orbit launch vehicle

Zhang

Wang

2017

Proceedings of the Institution of Mechanical Engineers, Part G:

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The liquid oxygen/methane staged cycle liquid-rocket engine is one of the most potential rocket engines in the future for its higher performance, higher fuel density and reusable capacity. Two working states of this liquid-rocket engine named as full-load state and half-load state are defined in this paper. Based on this liquid-rocket engine, a dual-rocket-basedcombined-cycle propulsion system with liquid oxygen /air/methane as propellants is therefore proposed. The dualrocket-based-combined-cycle system has then five working modes: the hybrid mode, pure ejector mode, ramjet mode, scramjet mode and pure rocket mode. In hybrid mode, the booster and ejector rockets driven by the full-load liquidrocket engine work together with the purpose of reducing thrust demand on ejector rocket. In scramjet mode, the fuelrich burned hot gas generated by the half-load liquid-rocket engine is used as fuel, which is helpful to reduce the technical difficulty of scramjet in hypersonic speed. The five working modes of dual-rocket-based-combined-cycle are highly integrated based on the full-or half-load state of the liquid oxygen/methane staged cycle liquid-rocket engine, and the unified single type fuel of liquid methane is adopted for the whole modes. Then a preliminary design of a horizontal takeoff two-stage-to-orbit launch vehicle is conducted based on the dual-rocket-based-combined-cycle propulsion system. Under an averaged baseline thrust and specific impulse, the launch trajectory to reach a low Earth orbit at 100 km is optimized via the pseudo-spectral method subject to maximizing the payload mass. It is shown that the two-stage-to-orbit vehicle based on the dual-rocket-based-combined-cycle can achieve the payload mass fraction of 0.0469 and 0.0576 for polar mission and equatorial mission, respectively. Conclusively, insights gained in this paper can be usefully applied to a more detailed design of the dual-rocket-based-combined-cycle powered two-stage-to-orbit launch vehicle.

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LOX/methane and LOX/kerosene high thrust engine trade-off

Cited by 24 publications

References 8 publications

A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines

A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines

A Reinforcement Learning Approach for Transient Control of Liquid Rocket Engines

Conceptual study of a dual-rocket-based-combined-cycle powered two-stage-to-orbit launch vehicle

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