Physical optimisation of ion thruster plume behaviour

离子推进器可用于各种太空任务，包括精确指向、轨道调整、星座控制和维护、碎片清除和深空探测。由于几次演示任务说明了它们的可靠性和成本效益，离子推进器领域和空间领域的电力推进领域的研究和发展有所增加。该研究项目的目标包括在推进器性能方面的总体效率和开发一种新的推力矢量机构。推力矢量将通过改变现有离子推进器的物理设计，进一步优化由离子离开推进器形成的羽流的扩散，从而进一步发展当前最先进的技术。由于推力矢量机制，这将有助于整体可能的任务应用。能够最大限度地减少或控制航天器周围等离子体鞘层的形成以及离子离开推进器引起的其他退化效应，将导致航天器运行更长时间。本研究旨在通过等离子体物理、数值模拟、人工智能和通用航空航天工程方法的混合，修改和优化当前最先进的离子推进器的设计，以最大限度地提高性能、效率和寿命。改进的离子推进器设计将通过设置一个初始标准来适应当前现有的立方体卫星尺寸，并评估以选择最有效的设计。这些模拟将在项目开始时开发的3D数值代码中进行，因此将进行一项研究，以选择最佳的数值方法来模拟系统中的等离子体物理。此外，人工智能的使用将在项目的后期进行探索，不仅可以进行设计优化，还可以进行一种时间序列预测，以预测由于长期使用离子推进器而导致的航天器鞘层形成和其他退化效应。本研究项目将解决以下问题：模拟离子推力器机制的最佳数值方法是什么？对于这种应用，粒子相互作用建模的最佳算法是什么？如何提高当前离子推进器技术的推进效率和羽流行为？新推进器中不同的推进剂对环境有什么影响？当在近地轨道上改变高度时，推进器的性能会如何变化？与现有的推进器相比如何？离子推力器的数值模拟对哪些参数最敏感？如何改进？该设计的新颖之处在于，它使用外部硬件来实现推力矢量，同时不需要对推进器进行任何重新设计。此外，人工智能的使用将是电力推进建模的一种新方法，可以观察离子推进器可能对航天器造成的退化影响，而无需进行大量的计算模拟。

Ion thrusters can be used on a variety of space missions, with applications including precision pointing, orbital adjustments, constellation control and maintenance, debris removal and deep-space exploration. Due to several demonstrator missions illustrating their reliability and cost benefits, there has been an increase in investigation and growth in the ion thruster sector and in the electric propulsion in space sector. The goals of this research project include the total overall efficiency in respect to the performance of the thruster and to develop a novel thrust vectoring mechanism. The thrust vectoring will further optimise the spread of the plume that is formed by the ions leaving the thruster, by changing the physical design of existing ion thrusters and therefore, further develop current state of the art technology. This will result in aiding overall possible mission application due to the thrust vectoring mechanism. Being able to minimize or control the formation of plasma sheath around a spacecraft and other degradation effects caused by the ions leaving the thruster, will result in the spacecraft being operational for a longer period.Aims and ObjectivesThis research aims to modify and optimise the current design of state-of-the-art ion thrusters, with amixture of plasma physics, numerical modelling, artificial intelligence, and general aerospace engineering approach to maximise performance, efficiency, and lifetime. Modified ion thruster designs will be proposed by setting an initial criterion to adapt to current existing CubeSat dimensions, and evaluated to choose the most efficient design. These simulations will be performed in a 3D numerical code which will be developed at the start of the project, and consequently a study will be performed to choose the optimum numerical methods to model the plasma physics in the system. Furthermore, the use of artificial intelligence will be explored later in the project, to perform not only design optimisations, but also a type of time-series forecasting to predict the sheath formation and other degradation effects present in the spacecraft caused by long-term use of an ion thruster. This research project will address the following questions:What is the best numerical method to simulate the ion thruster mechanism?What is the optimum algorithm for particle interaction modelling for this application?How can the propulsive efficiency and plume behaviour of current state of the art ion thruster technology be improved?What effect on the environment will different propellants in the new thruster have?How will the performance of the thruster vary whilst changing altitude in a low Earth orbit and how does this compare with existing thrusters?What parameters is the numerical simulation of an ion thruster most sensitive to and how can this be improved?MethodologyThe novelty in the proposed design is that it uses an external piece of hardware to enable thrust vectoring whilst not requiring any redesign of the thruster. Additionally, the use of AI would be a novel approach to electric propulsion modelling, to observe degradation effects over the spacecraft potentially caused by an ion thruster, without having to perform heavy computational simulations.