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

Joint Authors

Viganò, Davide
Annovazzi, Adriano
Maggi, Filippo

Source

International Journal of Aerospace Engineering

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-04-11

Country of Publication

Egypt

No. of Pages

8

Abstract EN

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.

American Psychological Association (APA)

Viganò, Davide& Annovazzi, Adriano& Maggi, Filippo. 2016. Monte Carlo Uncertainty Quantification Using Quasi-1D SRM Ballistic Model. International Journal of Aerospace Engineering،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1104994

Modern Language Association (MLA)

Viganò, Davide…[et al.]. Monte Carlo Uncertainty Quantification Using Quasi-1D SRM Ballistic Model. International Journal of Aerospace Engineering No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1104994

American Medical Association (AMA)

Viganò, Davide& Annovazzi, Adriano& Maggi, Filippo. Monte Carlo Uncertainty Quantification Using Quasi-1D SRM Ballistic Model. International Journal of Aerospace Engineering. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1104994

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1104994