Preliminary space mission design under uncertainty

This paper proposes a way to model uncertainties and to introduce them explicitly in the design process of a preliminary space mission. Traditionally, a system margin approach is used in order to take the min to account. In this paper, Evidence Theory is proposed to crystallise the inherent uncertainties. The design process is then formulated as an optimisation under uncertainties(OUU). Three techniques are proposed to solve the OUU problem: (a) an evolutionary multi-objective approach, (b) a step technique consisting of maximising the belief for different levels of performance, and (c) a clustering method that firstly identifies feasible regions.The three methods are applied to the Bepi Colombo mission and their effectiveness at solving the OUU problem are compared

Preliminary space mission design under uncertainty

This paper proposes a way to model uncertainties and to introduce them explicitly in the design process of a preliminary space mission. Traditionally, a system margin approach is used in order to take them into account. In this paper, Evidence Theory is proposed to crystallise the inherent uncertainties. The design process is then formulated as an Optimisation Under Uncertainties (OUU). Three techniques are proposed to solve the OUU problem: (a) an evolutionary multi-objective approach, (b) a step technique consisting of maximising the belief for different levels of performance, and (c) a clustering method that firstly identifes feasible regions. The three methods are applied to the BepiColombo mission and their effectiveness at solving the OUU problem are compared

Activities of the Space Advanced Research Team at the University of Glasgow

A wide range of technologies and methodologies for space systems engineering are currently being developed at the University of Glasgow. Much of the work is centred on mission analysis and trajectory optimisation, complemented by research activities in autonomous and multi-agent systems. This paper will summarise these activities to provide a broad overview of the current research interests of the Space Advanced Research Team (SpaceART). It will be seen that although much of the work is mission driven and focussed on possible future applications, some activities represent basic research in space systems engineering

Robust Mission Design Through Evidence Theory and Multi-Agent Collaborative Search

In this paper, the preliminary design of a space mission is approached introducing uncertainties on the design parameters and formulating the resulting reliable design problem as a multiobjective optimization problem. Uncertainties are modelled through evidence theory and the belief, or credibility, in the successful achievement of mission goals is maximised along with the reliability of constraint satisfaction. The multiobjective optimisation problem is solved through a novel algorithm based on the collaboration of a population of agents in search for the set of highly reliable solutions. Two typical problems in mission analysis are used to illustrate the proposed methodology

Space activities in Glasgow; advanced microspacecraft from Scotland

The City of Glasgow is renowned for its engineering and technological innovation; famous Glaswegian inventors and academics include James Watt (Steam Engine) and John Logie Baird (television), amongst many others. Contemporary Glasgow continues to pioneer and invent in a multitude of areas of science and technology and has become a centre of excellence in many fields of engineering; including spacecraft engineering. This paper will discuss how Clyde Space Ltd and the space groups at both Glasgow and Strathclyde Universities are combining their knowledge and expertise to develop an advanced microspacecraft platform that will enable a step change in the utility value of miniature spacecraft. The paper will also explore how the relationship between the academic and industrial partners works in practice and the steps that have been taken to harness resulting innovation to create space industry jobs within a city that was, until recently, void of any commercial space activity

Evidence-based robust design of deflection actions for near Earth objects

This paper presents a novel approach to the robust design of deflection actions for Near Earth Objects (NEO). In particular, the case of deflection by means of Solar-pumped Laser ablation is studied here in detail. The basic idea behind Laser ablation is that of inducing a sublimation of the NEO surface, which produces a low thrust thereby slowly deviating the asteroid from its initial Earth threatening trajectory. This work investigates the integrated design of the Space-based Laser system and the deflection action generated by laser ablation under uncertainty. The integrated design is formulated as a multi-objective optimisation problem in which the deviation is maximised and the total system mass is minimised. Both the model for the estimation of the thrust produced by surface laser ablation and the spacecraft system model are assumed to be affected by epistemic uncertainties (partial or complete lack of knowledge). Evidence Theory is used to quantify these uncertainties and introduce them in the optimisation process. The propagation of the trajectory of the NEO under the laser-ablation action is performed with a novel approach based on an approximated analytical solution of Gauss’ Variational Equations. An example of design of the deflection of asteroid Apophis with a swarm of spacecraft is presented

Hazardous near Earth asteroid mitigation campaign planning based on uncertain information on fundamental asteroid characteristics

Given a limited warning time, an asteroid impact mitigation campaign would hinge on uncertainty-based information consisting of remote observational data of the identified Earth-threatening object, general knowledge of near-Earth asteroids (NEAs), and engineering judgment. Due to these ambiguities, the campaign credibility could be profoundly compromised. It is therefore imperative to comprehensively evaluate the inherent uncertainty in deflection and plan the campaign accordingly to ensure successful mitigation. This research demonstrates dual-deflection mitigation campaigns consisting of primary (instantaneous/quasi-instantaneous) and secondary (slow-push) deflection missions, where both deflection efficiency and campaign credibility are taken into account. The results of the dual-deflection campaign analysis show that there are trade-offs between the competing aspects: the launch cost, mission duration, deflection distance, and the confidence in successful deflection. The design approach is found to be useful for multi-deflection campaign planning, allowing us to select the best possible combination of missions from a catalogue of campaign options, without compromising the campaign credibility

Uncertainty modelling in reliable preliminary space mission design

In the early phase of the design of a space mission, it is generally desirable to investigate as many feasible alternative solutions as possible. At this particular stage, an insufficient consideration for uncertainty would lead to a wrong decision on the feasibility of the mission. Traditionally a system margin approach is used in order to take into account the inherent uncertainties within the subsystem budgets. The reliability of the mission is then independently computed in parallel. An iteration process between the solution design and the reliability assessment should finally converge to an acceptable solution. By combining modern statistical methods to model uncertainties and global search techniques for multidisciplinary design, the present work proposes a way to introduce uncertainties in the mission design problem formulation. By minimising the effect of these uncertainties on both constraints and objective functions, while optimising the mission goals, the aim is to increase the reliability of the produced results

Robustness and Adaptiveness Analysis of Future Fleets

Making decisions about the structure of a future military fleet is a challenging task. Several issues need to be considered such as the existence of multiple competing objectives and the complexity of the operating environment. A particular challenge is posed by the various types of uncertainty that the future might hold. It is uncertain what future events might be encountered; how fleet design decisions will influence and shape the future; and how present and future decision makers will act based on available information, their personal biases regarding the importance of different objectives, and their economic preferences. In order to assist strategic decision-making, an analysis of future fleet options needs to account for conditions in which these different classes of uncertainty are exposed. It is important to understand what assumptions a particular fleet is robust to, what the fleet can readily adapt to, and what conditions present clear risks to the fleet. We call this the analysis of a fleet's strategic positioning. This paper introduces how strategic positioning can be evaluated using computer simulations. Our main aim is to introduce a framework for capturing information that can be useful to a decision maker and for defining the concepts of robustness and adaptiveness in the context of future fleet design. We demonstrate our conceptual framework using simulation studies of an air transportation fleet. We capture uncertainty by employing an explorative scenario-based approach. Each scenario represents a sampling of different future conditions, different model assumptions, and different economic preferences. Proposed changes to a fleet are then analysed based on their influence on the fleet's robustness, adaptiveness, and risk to different scenarios

Robustness and Adaptability Analysis of Future Military Air Transportation Fleets

Making decisions about the structure of a future military fleet is challenging. Several issues need to be considered, including multiple competing objectives and the complexity of the operating environment. A particular challenge is posed by the various types of uncertainty that the future holds. It is uncertain what future events might be encountered and how fleet design decisions will influence these events. In order to assist strategic decision-making, an analysis of future fleet options needs to account for conditions in which these different uncertainties are exposed. It is important to understand what assumptions a particular fleet is robust to, what the fleet can readily adapt to, and what conditions present risks to the fleet. We call this the analysis of a fleet’s strategic positioning. Our main aim is to introduce a framework that captures information useful to a decision maker and defines the concepts of robustness and adaptability in the context of future fleet design. We demonstrate our conceptual framework by simulating an air transportation fleet problem. We account for uncertainty by employing an explorative scenario-based approach. Each scenario represents a sampling of different future conditions and different model assumptions. Proposed changes to a fleet are then analysed based on their influence on the fleet’s robustness, adaptability, and risk to different scenarios