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

Dataset supporting the Scitech 2017 conference paper.

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 small, solid-fuelled, unguided rockets. 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.