The Mars Shuttle

Abstract

The last 20 years has brought with it a surge in efforts toward the Red Planet as the next frontier is human space exploration draws closer. Many concepts have been proposed for a sustained human settlement on Mars, with NASA’s ISRU-to-the-wall campaign identifying the need for a shuttle vehicle between theMartian surface and a station in an orbit around the planet. Two such vehicle concepts have been designed: the Charon by Gaffarel et. al. and Hercules by Komar et. al.. However a Multidisciplinary Design Optimisation (MDO) has thus far not been applied. In this research an MDO is employed for the same mission scenario as the Charon vehicle’s. The vehicle must transport 1200 kg, including 6 crew, to a 607 km circular orbit at 44.96± inclination from the Martian base that is located at 42.5± North and 25.5± East. It must then return to the base, its entry beginning at 80 km altitude at a velocity of 3500 m/s. The MDO in this research is performed by dividing the design of the vehicle and its trajectories into various disciplines, which are optimised in parallel. In reality cost commonly is the dominant factor that drives the design, in this case, the vehicle’s Gross Take OffWeight (GTOW) is taken as the objective. Estimating the cost of the Martian shuttle vehicle within reasonable accuracy is exceedingly difficult, as not only is its realisation still decades away, costs such as the shuttle’s transportation to Mars, its operational costs, and its maintenance costs are very hard to estimate. However, a vehicle’s GTOW is directly influential on its cost, and its reduction is therefore the optimisation’s goal. The disciplines within the optimisation are the vehicle’s geometry, mass, aerodynamics, and ascent and descent trajectories. Constraints are set for both the vehicle and its trajectories, to which the design must adhere, and the performance of the design is determined by a fitness function that ensures the reduction of the vehicle’s GTOW. The optimiser itself is written using Tudat software, a set of C++ libraries developed by the TU Delft. As the same mission scenario is taken for the vehicle in this research as that of the Charon vehicle, the Charon design can be directly compared to that of the optimiser. TheMDO is able to significantly reduce the vehicle GTOW, obtaining an optimum solution of 146.2 tonnes, which is more than 20 tonnes lighter than Charon, at 168.1 tonnes. The greatest reduction in mass is found in the ascent propellant mass, which is the greatest contributor to the GTOW. This reduction is mostly due to the lower maximum Thrust to Weight (TW) ratio used in the MDO. Other scenarios are also investigated and their effects observed. Two other target orbits and rendezvous strategies are tested, namely the same as the Hercules vehicle (108 km pericentre altitude and an eccentricity of 0.0178), and a direct ascent to the orbital node at a circular 500 km altitude orbit. The Hercules vehicle scenario proved to be by far the most GTOW-preferable, with a GTOW of only 103.0 tonnes. The GTOW of the MDO solution found for the Hercules scenario is also less than that of the Hercules vehicle design, which is 162.8 tonnes, however the Hercules vehicle transports a payload mass of 5750 kg as opposed to the MDO’s 1200 kg, therefore the mass reductions cannot be solely attributed to the optimiser performance. It is clear from the results that the altitude of the initial target orbit is the greatest factor contributing to the GTOW, with a reduction in both payload mass andMartian base latitude also shown to reduce the GTOW. Neither an increase in the maximum acceleration constraint, nor a change in ascent thrust profile, were shown to have any benefit on the GTOW. The sensitivity of the optimum design with respect to uncertainties is assessed. The final pericentre and final eccentricity are both most sensitive to the final pitch node value, especially when taking interference with other variables into account. The inclination, however, was almost solely influenced by the first pitch angle value. The latitude and longitude are also almost solely influenced by a single variable, namely the flight path angle, and the final velocity and final pitch angle are both highly volatile to all variables when interference effects are taken into account. TheMDO model as a whole is found to be sensitive to changes in both aerodynamics coefficients and propulsive efficiency; an increase in aerodynamic coefficients adversely affects the GTOW, and an increase in propulsive efficiency benefits the GTOW, and vice versa.