Investigating the Effect of Geometrical Parameters on the Performance of a Thrust Measurement Stand and Optimizing its Design Using Genetic Algorithm

Document Type : Dynamics, Vibrations, and Control

Authors

1 Corresponding author: Researcher, Space Thrusters Research Institute, Iranian Space Research Center, Tabriz, Iran

2 Assistant Professor, Space Thrusters Research Institute, Iranian Space Research Center, Tabriz, Iran

3 Researcher, Space Thrusters Research Institute, Iranian Space Research Center, Tabriz, Iran

Abstract

In this paper, the influence of the geometric parameters of a thrust measurement stand in mN level and for electrical thrusters on its performance is investigated. To measure the thrust of the electrical thrusters, a system must be used that separates the thrust force from the weight force. Thus, thrust measurement systems are designed based on a pendulum. The geometric parameters of a thrust measurement stand, such as the length of arms, the mass of different parts, and the stiffness of pivots affect the overall performance of the system, including its dynamic and static response (for example, displacement, natural frequency and stabilization time of oscillations). For this purpose, primarily, the analytical model for the behavior of a thrust measurement stand with an inverted pendulum configuration is obtained. Then, using the obtained results, the optimal design of several stands is carried out based on the specified physical requirements and using the Genetic Algorithm method. Finally, an experimental thrust measurement stand with a maximum measuring thrust of 100 mN is developed based on obtained specifications from the optimization and by validating the results of the analytical model, the error of the model is estimated to be less than 6 percent.

Highlights

  • Analytical modeling of dynamic and static behavior of a thrust measurement stand
  • Specifying the importance and influence of the geometric parameters of the stand on its performance
  • Optimal Designing based on the Genetic Algorithm method
  • Developing an experimental stand and verifying

Keywords

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References

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Aerospace Mechanics
Volume 19, Issue 1 - Serial Number 71
Serial No. 71, Spring Quarterly
June 2023
Pages 107-121

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History

  • Receive Date: 19 September 2022
  • Revise Date: 25 October 2022
  • Accept Date: 06 November 2022
  • Publish Date: 09 April 2023

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