Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-28T15:48:08.321Z Has data issue: false hasContentIssue false
  • English
  • Français

A 3D particle model for the plume CEX simulation

Published online by Cambridge University Press:  17 July 2018

C. Lu ,
P. Qiu ,
Y. Cao ,
T.P. Zhang  and
J.J. Chen
C. Lu
Affiliation:
Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, P.R. China
P. Qiu
Affiliation:
Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, P.R. China
Y. Cao*
Affiliation:
Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, P.R. China
T.P. Zhang
Affiliation:
Lanzhou Institute of Physics, Lanzhou, P.R. China
J.J. Chen
Affiliation:
Lanzhou Institute of Physics, Lanzhou, P.R. China
*
[email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Charge Exchange (CEX) ion is the main factor causing the plume pollution. The distribution of CEX ions is determined by the distribution of beam ions and neutral atoms. Hence, the primary problem in the study of the plume is how to accurately simulate the distribution of beam ions and neutral atoms. At present, the most commonly used model utilised for the plume simulation is the analytical model proposed by Roy for the plume simulation of the NASA Solar Technology Application Readiness (NSTAR) ion thruster. However, this analytical model can only be applied to the ion beam with small divergence angles. In addition, the analytical model is no longer applicable to the simulation for the plume of a new type of ion thruster that appeared recently, which is called the annular ion thruster. In this paper, a 3D particle model is proposed for the plume simulation of ion thrusters consisting of the particle model for beam ions, the Direct Simulation Monte Carlo (DSMC) model for neutral atoms and the Immersed Finite Element-Particle In Cell-Monte Carlo Collision (IFE-PIC-MCC) model for CEX ions. Then, the plume of the NSTAR ion thruster is simulated by both Roy's model and the 3D particle model. The simulation results of both models are then compared with the experimental results. It is shown that the numerical results of the 3D particle model agree well with those of the analytical model and the experimental data. And this 3D particle model can also be used for other electric thrusters.

Keywords

Ion thrusterplume3D particle modelIFE-PIC-MCC
Type
Research Article
Information
The Aeronautical Journal , Volume 122 , Issue 1255 , September 2018 , pp. 1425 - 1441
Copyright
Copyright © Royal Aeronautical Society 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

These authors equally contributed to the work

References

REFERENCES

1.Samanta Roy, R.I., Hastings, D.E. and Gatsonis, N.A. Modelling of ion thruster plume contamination, 30th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 27-29 June, Indianapolis, Indiana, US, AIAA 1994-3138.Google Scholar
2.Stephani, K.A., Boyd, I.D., Balthazor, R.L., Mcharg, M.G., Ueller, B.A. and Adams, R.J. Analysis and observation of spacecraft plume/ionosphere interactions during maneuvers of the space shuttl, J Geophysical Research: Space Physics, 2014, 119, (9), pp 7636–7648.Google Scholar
3.King, L.B., Parker, G.G., Deshmukh, S. and Chong, J.H. Study of interspacecraft coulomb forces and implications for formation flying, J Propulsion and Power, 2003, 19, (3), pp 497–505.Google Scholar
4.Shan, K., Chu, Y., Li, Q., Zheng, L. and Cao, Y. Numerical Simulation of Interaction between Hall Thruster CEX Ions and SMART-1 Spacecraft, Mathematical Problems in Engineering, 2015, (3), pp 1–8.Google Scholar
5.Samanta Roy, R.I. Numerical simulation of ion thruster plume backflow for spacecraft contamination assessment, Massachusetts Institute of Technology, 1995.Google Scholar
6.Bird, G.A. Molecular gas dynamics and the direct simulation Monte Carlo of gas flows, Clarendon, Oxford, 1994, 508, p 128.Google Scholar
7.Wang, J., Brinza, D. and Young, M. Three-dimensional particle simulations of ion propulsion plasma environment for deep space 1t, J Spacecraft and Rockets, 2001, 38, (3), pp 433–440.Google Scholar
8.Patterson, M.J., Herman, D., Shastry, R., Noord, J.V. and Foster, J.E. Annular-geometry ion engine: Concept, development status, and preliminary performance, 48th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 30 July-1 August, Atlanta, Georgia, US, AIAA 2012-3798.Google Scholar
9.Han, D. and Wang, J.J. Simulations of ion thruster plume contamination with a whole grid sputtered Mo source model, 49th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 14-17 July, San Jose, California, US, AIAA 2013-3888.Google Scholar
10.Wang, J., Han, D. and Hu, Y. Kinetic simulations of plasma plume potential in a vacuum chamber, IEEE Transactions on Plasma Science, 2015, 43, (9), pp 3047–3053.Google Scholar
11.Tajmar, M., Gonzalez, J. and Hilgers, A. Modeling of spacecraft-environment interactions on SMART-1, J Spacecraft and Rockets, 2001, 38, (3), pp 393–399.Google Scholar
12.Markelov, G. and Gengembre, E. Modeling of plasma flow around SMART-1 spacecraft, IEEE Transactions on Plasma Science, 2006, 34, (5), pp 2166–2175.Google Scholar
13.Boyd, I.D. Numerical simulation of Hall thruster plasma plumes in space, IEEE Transactions on Plasma Science, 2006, 34, (5), pp 2140–2147.Google Scholar
14.Kafafy, R. and Cao, Y. Modelling ion propulsion plume interactions with spacecraft in formation flight, The Aeronautical J, 2010, 114, (1157), pp 417–426.Google Scholar
15.Kafafy, R., Lin, T., Lin, Y. and Wang, J. Three-dimensional immersed finite element methods for electric field simulation in composite materials, Int J Numerical Methods Engineering, 2005, 64, (7), pp 940–972.Google Scholar
16.Wang, J., Cao, Y., Kafafy, R., Pierru, J. and Decyk, V.K. Simulations of ion thruster plume–spacecraft interactions on parallel supercomputer, IEEE Transactions on Plasma Science, 2006, 34, (5), pp 2148–2158.Google Scholar
17.Wangy, J., Cao, Y., Kafafy, R. and Decyk, V.K. Electric propulsion plume simulations using parallel computer, Scientific Programming, 2007, 15, (2), pp 83–94.Google Scholar
18.Samanta Roy, R.I., Hastings, D.E. and Gastonis, N.A. Ion-thruster plume modeling for backflow contamination, J Spacecraft and Rockets, 1996, 33, (4), pp 525–534.Google Scholar
19.David, O., Benson, S., Witzberger, K. and Cupples, M. Deep space mission applications for NEXT: NASA’s evolutionary xenon thrusterr, 40th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 11-14 July, Fort Lauderdale, Florida, US, AIAA 2004-3806.Google Scholar
20.Shastry, R., Herman, D.A., Soulas, G.C. and Patterson, M.J. Status of NASA’s Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 50,000 h and 900 kg Throughput, 33rd International Electric Propulsion Conference, IEPC-2013-121, Washington, DC, US, 6-10 October 2013.Google Scholar
21.Boyd, I.D., Van Gilder, D.B. and Liu, X. Monte Carlo simulation of neutral xenon flows in electric propulsion devices, J Propulsion and Power, 1998, 14, (6), pp 1009–1015.Google Scholar
22.Shastry, R., Patterson, M.J., Herman, D.A. and Foster, J.E. Current density measurements of an annular-geometry ion engine, 48th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 30 July-1 August, Atlanta, Georgia, US, AIAA 2012-4186.Google Scholar
23.Patterson, M.J., Foster, J.E., Young, J.A. and Crofton, M.W. Annular engine development status, AIAA Paper, 2013, 3892.Google Scholar