Analysis, Optimization and Probabilistic Assessment of an Airbag Landing System for the ExoMars Space Mission

Vented airbag systems offer an attractive means of cushioning the landing impact of robotic planetary spacecraft. This type of airbag absorbs the impact kinetic energy by exhausting the inflation gas through vent patches in a controlled way that aims to bring the lander to rest with minimum rebound, limited deceleration and in an upright attitude. Such systems are characterised by highly non-linear behaviour. This, coupled with the difficulty of adequate terrestrial testing results in an analytical approach to design that relies on explicit finite element (FE) analysis. However, the simulation of an impact of a few tenths of a second duration typically requires tens of hours of CPU time, making it impractical to optimise a design using a trial end error approach and to perform the large number of analysis runs necessary for a probabilistic assessment of varied landing conditions. This paper presents a methodology for overcoming these problems with reference to a vented airbag design for the ESA ExoMars mission. The approach utilises the Moving Least Squares Method (MLSM) to fit high quality approximations to multi-dimensional response surfaces from a relatively small number of FE analysis runs. This method is well-adapted to highly non-linear and noisy response surfaces that are typical for this problem. The surrogate response surfaces were used to locate an optimum in the design parameter space and to perform 10,000 sample point Monte Carlo runs in a probabilistic assessment of reliability due to varying landing conditions.