Ascend trajectory simulation and optimizer for space-launcher systems and space-crafts. TrackJack's origin is part of a diploma thesis in Aerospace Engineering at the University of Applied Sciences Bremen.
Contact Andreas Hornig for details.
Trajectory Optimization 101
In the current version TrackJack is able to find an ascent trajectory (flight path) for a launcher rocket into the target orbit.
The found control-function leads to a continous trajectory between the existing boundary values for start and target conditions and is done in respect to gravity turn condition and aerodynamic drag. This is important to minimize the lost thrust for steering that can't be used for direct translative acceleration, because gravity will bend the rocket's trajectory. By only fulfilling gravity turn condition it would bend the trajectory to tangent into deeper atmosperic regions, so the atmosphere will lead to a high aerodynamic drag that will decellerate the rocket. So the finder algorithm will find a trajectory that is a compromise between these and even more conditions.
This is done according to the equations of motion on a 2D plane. The finder algorithm changes the thrust vector, that controlls the steered direction, and finds the best thrust vector angle at any discrete time-step. This is repeated for each time-step until all thrust vector angles are found for the complete flight-time and the controll-function is formed.
Scientific Goal and Future Features
TrackJack's goal is to solve problems during ascent, interplanetary and re-entry trajectories.
The first step will be to validate data analysed for the diploma thesis this app derived from to be sure, that the BOINC-app will lead to correct results.
The next step will be to add new features to TrackJack that will allow new trajectory forms like interplanetary missions and re-entry paths. When this is achieved on of the first tasks will be to find a thrust-profile for the sounding rocket that is designed by DGLR-Group HyEnD - Hybrid Engine Development.
TrackJack is a single-core application using Java JRE (Java Runtime Environment) and 7-Zip compression for app and workunits.
The idea behind extreme machines is not to create a huge, multimillion ton machine, rather an extremely optimized device, under the realms of very classical mechanics, to perform specific tasks.
Presently the project is handling the following:
Contact Sayandeep Khan for details.
- Simulation of a wheel, optimized for performing in lunar environment. From Lunakhod and the Apollos, it is known, that a slowly turning, deformable wheel perform best in lunar regolith, but no detail model exists. This wheel, is being developed as part of the developments carried out by Team Synergy Moon, google lunar x prize team
- The other idea is to test the limits of classical physics. Although probably the last unsolved problem in the classical mechanics we know is the search for smooth sollution of NS equation in turbulant flow, extraterrestrial material might offer us a new challenge. The moon material is relative less well studied than material from earth.
We want to compare the results of our simulation with the real performance of the MoonRover, perhaps that will show us how material interacts in lunar environment, and give us more insight in classical physics.