Preliminary design of helicon plasma thruster by means of particle swarm optimization

被引:5
|
作者
Coppola, G. [1 ]
Panelli, M. [1 ]
Battista, F. [1 ]
机构
[1] Italian Aerosp Res Ctr, CIRA, Via Maiorise, I-81043 Capua, CE, Italy
关键词
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
D O I
10.1063/5.0149430
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Radio-frequency and Helicon Plasma Thrusters have emerged as viable electric propulsion systems due to their high plasma density, thrust density, and useful life. Helicon Plasma Thruster (HPT) is a very attractive technology because it could use many propellants and does not require hollow cathodes or grids, overcoming their associated critical erosion problem and extending the thruster's lifetime to some tens of thousands of hours. Despite the fact that high-power HPTs have reached 30% efficiency in laboratory configurations, sophisticated numerical models are required for a deeper understanding of the main plasma phenomena and for the preliminary design to increase the very low HPT's efficiency (3-7%) typical of the low-power class thrusters. The paper focuses on the development of a model for the low-medium power range (50-2000 W) of HPTs design. Starting from Lafleur's model, it has been improved with the hypothesis of neutral gas being expelled at the real thruster's wall operative temperature (300-600 K) in place of the more frequent laboratory temperature assumption (300 K). This hypothesis affects total thrust and specific impulse by about 10%. A parametric analysis of the slenderness ratio (chamber length-to-radius) has been conducted. The results showed that slender configurations lead to higher efficiencies. Downstream from the numerical model validation, a tool for the global design has been built with the Particle Swarm Optimization (PSO) technique that leads to optimal thruster configuration. This tool has been used to design a 4 mN HPT tuning the PSO in order to minimize the dimensions and the weight according to the assigned mission constraints (i.e., power, thrust, and weight). A total efficiency of 10.4% results. (c) 2023 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页数:15
相关论文
共 50 条
  • [21] PARTICLE SWARM METHODOLOGIES FOR ENGINEERING DESIGN OPTIMIZATION
    Rao, Singiresu S.
    Annamdas, Kiran K.
    PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, VOL 5, PTS A AND B: 35TH DESIGN AUTOMATION CONFERENCE, 2010, : 507 - 516
  • [22] Particle swarm optimization for mobile network design
    El-Saleh, Ayman A.
    Ismail, Mahamod
    Viknesh, R.
    Mark, C. C.
    Chan, M. L.
    IEICE ELECTRONICS EXPRESS, 2009, 6 (17): : 1219 - 1225
  • [23] A particle swarm algorithm for multiobjective design optimization
    Ochlak, Eric
    Forouraghi, Babak
    ICTAI-2006: EIGHTEENTH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2006, : 765 - +
  • [24] Optimal Radome Design with Particle Swarm Optimization
    Chiba, Hidetoshi
    Inasawa, Yoshio
    Miyashita, Hiroaki
    Konishi, Yoshihiko
    2008 IEEE ANTENNAS AND PROPAGATION SOCIETY INTERNATIONAL SYMPOSIUM, VOLS 1-9, 2008, : 2886 - 2889
  • [25] Design and simulation of an Improved Particle Swarm Optimization
    Wei Jian-xiang
    Sun Yue-hong
    INFORMATION TECHNOLOGY FOR MANUFACTURING SYSTEMS, PTS 1 AND 2, 2010, : 1280 - +
  • [26] Particle swarm optimization in reactor core design
    Domingos, RP
    Schirru, R
    Pereira, CMNA
    NUCLEAR SCIENCE AND ENGINEERING, 2006, 152 (02) : 197 - 203
  • [27] Particle swarm approach for structural design optimization
    Perez, R. E.
    Behdinan, K.
    COMPUTERS & STRUCTURES, 2007, 85 (19-20) : 1579 - 1588
  • [28] Array design with accelerated particle swarm optimization
    1600, AMSE Press, 16 Avenue Grauge Blanche, Tassin-la-Demi-Lune, 69160, France (57):
  • [29] Particle Swarm Optimization for Structural Design Problems
    Saruhan, Hamit
    PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, 2010, 16 (02): : 207 - 212
  • [30] Particle evolutionary swarm for design reliability optimization
    Zavala, AEM
    Diharce, ERV
    Aguirre, AH
    EVOLUTIONARY MULTI-CRITERION OPTIMIZATION, 2005, 3410 : 856 - 869