Monte Carlo Uncertainty Quantification Using Quasi-1D SRM Ballistic Model

Author:

Viganò Davide1ORCID,Annovazzi Adriano2,Maggi Filippo1ORCID

Affiliation:

1. Department of Aerospace Science and Technology, SPLab, Politecnico di Milano, 20156 Milan, Italy

2. Space Propulsion Design Department, AVIO S.p.A., 00034 Colleferro, Italy

Abstract

Compactness, reliability, readiness, and construction simplicity of solid rocket motors make them very appealing for commercial launcher missions and embarked systems. Solid propulsion grants high thrust-to-weight ratio, high volumetric specific impulse, and a Technology Readiness Level of 9. However, solid rocket systems are missing any throttling capability at run-time, since pressure-time evolution is defined at the design phase. This lack of mission flexibility makes their missions sensitive to deviations of performance from nominal behavior. For this reason, the reliability of predictions and reproducibility of performances represent a primary goal in this field. This paper presents an analysis of SRM performance uncertainties throughout the implementation of a quasi-1D numerical model of motor internal ballistics based on Shapiro’s equations. The code is coupled with a Monte Carlo algorithm to evaluate statistics and propagation of some peculiar uncertainties from design data to rocker performance parameters. The model has been set for the reproduction of a small-scale rocket motor, discussing a set of parametric investigations on uncertainty propagation across the ballistic model.

Publisher

Hindawi Limited

Subject

Aerospace Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Performance prediction method of solid rocket motor based on the ground test;Journal of Physics: Conference Series;2024-08-01

2. 节流式燃氧分离固体发动机准一维内弹道数值研究;Acta Mechanica Sinica;2023-10-12

3. Prediction of Tail-Off Pressure Peak Anomaly on Small-Scale Rocket Motors;Aerospace;2023-02-13

4. Research on the Internal Ballistic Performance Prediction of Solid Rocket Motor Based on Monte Carlo;2021 12th International Conference on Mechanical and Aerospace Engineering (ICMAE);2021-07-16

5. Uncertainty analysis and design optimization of solid rocket motors with finocyl grain;Structural and Multidisciplinary Optimization;2020-09-02

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