Establishing a framework to explore the Servicer-Client relationship in On-Orbit Servicing

Abstract

On-Orbit Servicing (OOS) is becoming more extensively discussed in research and commercial developments. The key point of servicing relies on the relation between two systems, the Servicer executing the tasks and the Client being serviced. With the increase of interest in OOS applications, the exploration of the Client-Servicer relationship in different scenarios becomes a necessary step in servicing implementation. Exploring such a relationship involves translating the information available about OOS into useful inputs for spacecraft design, a challenging task due to the variety of applications and possible interactions between both sides. Then, different modelling and simulation techniques can be used to model and to explore the interaction of such complex systems for different scenarios of servicing. This paper presents an agent-based framework to explore the relations of Servicer and Client for applications of On-Orbit Servicing. To do so, the case for a hypothetical satellite operator is explored, under a specific set of requirements and conditions for different servicing solutions. First, the Agent Based Modelling and Simulation (ABMS) is established based on a specific set of rules, definition metrics and operation characteristics relating Servicer and Client. Then, the basic assumptions of Client, Servicer and servicing operations are discussed and the initial simulation parameters are defined. The ABMS is used to simulate OOS for a fleet of geostationary communication satellites for the cases of Lifetime Extension, Refuel and Rescue and Recover. In the end, the ABMS outputs are used to explore the design aspects of the Servicer and Client satellites at systems level. The results highlight the advantages of having this type of framework for early assessment of OOS under different types of context for both Servicer and Client. The paper concludes with directions of how the framework can be used to explore more complex and realistic scenarios of OOS, and assess their potential benefits.