Constrained optimisation of preliminary spacecraft configurations under the design-for-demise paradigm

In the past few years, the interest towards the implementation of design-for-demise measures has increased steadily. The majority of mid-sized satellites currently launched and already in orbit fail to comply with the casualty risk threshold of 10−4. Therefore, satellites manufacturers and mission operators need to perform a disposal through a controlled re-entry, which has a higher cost and increasead complexity. Through the design-for-demise paradigm, these additional cost and complexity can be removed as the spacecraft is directly compliant with the casualty risk regulations. However, building a spacecraft such that most of its parts will demise may lead to designs that are more vulnerable to space debris impacts, thus compromising the reliability of the mission. In fact, the requirements connected to the demisability and the survivability are in general competing. Given this competing nature, trade-off solutions can be found, which favour the implementation of design-for-demise measures while still maintaining the spacecraft resilient to space debris impacts. A multi-objective optimisation framework has been developed by the authors in previous works. The framework's objective is to find preliminary design solutions considering the competing nature of the demisability and the survivability of a spacecraft since the early stages of the mission design. Multi-objective optimisation is used to explore the large search space of the possible configurations in order to find a range of optimised trade-off solutions that can be used for the future phases of the mission design process. In this way, a more integrated design can be achieved. The present work focuses on the improvement of the multi-objective optimisation framework by including constraints. The constraints can be applied to the configuration of the spacecraft, with limitations on the location of the internal components, or to specific components, based on their feasibility and design. The evaluation of the demisability and survivability is carried out with two dedicated models, and the fitness of the solution is assessed through two indices summarising the level of demisability and survivability.