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An open-source, stochastic, six-degrees-of-freedom rocket flight simulator, with a probabilistic trajectory analysis approach

An open-source, stochastic, six-degrees-of-freedom rocket flight simulator, with a probabilistic trajectory analysis approach
An open-source, stochastic, six-degrees-of-freedom rocket flight simulator, with a probabilistic trajectory analysis approach
Predicting the flight-path of an unguided rocket can help overcome unnecessary risks. Avoiding residential areas or a car-park can improve the safety of launching a rocket significantly. Furthermore, an accurate landing site prediction facilitates recovery. This paper introduces a six-degrees-of-freedom flight simulator for large unguided model rockets that can fly to altitudes of up to 13 km and then return to earth by parachute. The open-source software package assists the user with the design of rockets, and its simulation core models both the rocket flight and the parachute descent in stochastic wind conditions. Furthermore, the uncertainty in the input variables propagates through the model via a Monte Carlo wrapper, simulating a range of possible flight conditions. The resulting trajectories are captured as a Gaussian process, which assists in the statistical assessment of the flight conditions in the face of uncertainties, such as changes in wind conditions, failure to deploy the parachute, and variations in thrust. This approach also facilitates concise presentation of such uncertainties via visualisation of trajectory ensembles.
1-15
American Institute of Aeronautics and Astronautics
Eerland, Willem
7f5826c3-536f-4fdc-955e-0f9870c96a0e
Box, Simon
2bc3f3c9-514a-41b8-bd55-a8b34fd11113
Fangohr, Hans
9b7cfab9-d5dc-45dc-947c-2eba5c81a160
Sobester, Andras
096857b0-cad6-45ae-9ae6-e66b8cc5d81b
Eerland, Willem
7f5826c3-536f-4fdc-955e-0f9870c96a0e
Box, Simon
2bc3f3c9-514a-41b8-bd55-a8b34fd11113
Fangohr, Hans
9b7cfab9-d5dc-45dc-947c-2eba5c81a160
Sobester, Andras
096857b0-cad6-45ae-9ae6-e66b8cc5d81b

Eerland, Willem, Box, Simon, Fangohr, Hans and Sobester, Andras (2017) An open-source, stochastic, six-degrees-of-freedom rocket flight simulator, with a probabilistic trajectory analysis approach. In AIAA Modeling and Simulation Technologies Conference. American Institute of Aeronautics and Astronautics. pp. 1-15 . (doi:10.2514/6.2017-1556).

Record type: Conference or Workshop Item (Paper)

Abstract

Predicting the flight-path of an unguided rocket can help overcome unnecessary risks. Avoiding residential areas or a car-park can improve the safety of launching a rocket significantly. Furthermore, an accurate landing site prediction facilitates recovery. This paper introduces a six-degrees-of-freedom flight simulator for large unguided model rockets that can fly to altitudes of up to 13 km and then return to earth by parachute. The open-source software package assists the user with the design of rockets, and its simulation core models both the rocket flight and the parachute descent in stochastic wind conditions. Furthermore, the uncertainty in the input variables propagates through the model via a Monte Carlo wrapper, simulating a range of possible flight conditions. The resulting trajectories are captured as a Gaussian process, which assists in the statistical assessment of the flight conditions in the face of uncertainties, such as changes in wind conditions, failure to deploy the parachute, and variations in thrust. This approach also facilitates concise presentation of such uncertainties via visualisation of trajectory ensembles.

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More information

Accepted/In Press date: 30 August 2016
e-pub ahead of print date: 5 January 2017
Published date: 9 January 2017
Organisations: Computational Engineering & Design Group

Identifiers

Local EPrints ID: 404214
URI: https://eprints.soton.ac.uk/id/eprint/404214
PURE UUID: 3b60b64f-1b4f-4118-9170-179f3bdfa0cb
ORCID for Willem Eerland: ORCID iD orcid.org/0000-0002-4559-6122
ORCID for Andras Sobester: ORCID iD orcid.org/0000-0002-8997-4375

Catalogue record

Date deposited: 09 Jan 2017 08:45
Last modified: 14 Mar 2019 01:45

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