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

In the past few years, the interest towards the implementation of design-fordemise 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 ∗Corresponding author Email addresses: mirko.trisolini@polimi.it (Mirko Trisolini), H.G.Lewis@soton.ac.uk (Hugh G. Lewis), camilla.colombo@polimi.it (Camilla Colombo) 1Present address: Politecnico di Milano, Via La Masa 34, 20156, Milano, Italy Preprint submitted to Journal of Space Safety Engineering January 6, 2021 ar X iv :2 10 1. 01 55 8v 1 [ ee ss .S Y ] 2 7 D ec 2 02 0 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.

[1]  Shannon Ryan,et al.  Micrometeoroid and Orbital Debris (MMOD) Shield Ballistic Limit Analysis Program , 2010 .

[2]  N. Welty,et al.  Computational methodology to predict satellite system-level effects from impacts of untrackable space debris , 2013 .

[3]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[4]  R. K. Ursem Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[5]  F. Angrilli,et al.  The Inter-Agency Space Debris Coordination Committee (iadc) Protection Manual , 2005 .

[6]  Hugh G. Lewis,et al.  Spacecraft design optimisation for demise and survivability , 2018, Aerospace Science and Technology.

[7]  Kalyanmoy Deb,et al.  Simulated Binary Crossover for Continuous Search Space , 1995, Complex Syst..

[8]  James R. Wertz,et al.  Space Mission Analysis and Design , 1992 .

[9]  Jeffrey A. Hoffman,et al.  Illustrative NASA Low Earth Orbit spacecraft subsystems design-for-demise trade-offs, analyses and limitations , 2012 .

[10]  Johannes Gelhaus,et al.  Satellite vulnerability to space debris – an improved 3D risk assessment methodology , 2014 .

[11]  Kalyanmoy Deb,et al.  Analysing mutation schemes for real-parameter genetic algorithms , 2014, Int. J. Artif. Intell. Soft Comput..

[12]  Hugh G. Lewis,et al.  Demisability and survivability sensitivity to design-for-demise techniques , 2018, 1910.06397.

[13]  Camilla Colombo,et al.  Predicting the vulnerability of spacecraft components: modelling debris impact effects through vulnerable-zones , 2020, ArXiv.

[14]  Carlos A. Coello Coello,et al.  THEORETICAL AND NUMERICAL CONSTRAINT-HANDLING TECHNIQUES USED WITH EVOLUTIONARY ALGORITHMS: A SURVEY OF THE STATE OF THE ART , 2002 .

[15]  M. Lambert,et al.  Ballistic limit equation for equipment placed behind satellite structure walls , 2008 .

[16]  Marc Parizeau,et al.  DEAP: evolutionary algorithms made easy , 2012, J. Mach. Learn. Res..

[17]  Jeffrey A. Hoffman,et al.  Spacecraft Design-for-Demise implementation strategy & decision-making methodology for low earth orbit missions , 2013 .

[18]  George Studor,et al.  Handbook for Designing MMOD Protection , 2009 .

[19]  Hugh G. Lewis,et al.  Demise and Survivability Criteria for Spacecraft Design Optimization , 2016 .

[20]  Ali Gülhan,et al.  About the demisability of propellant tanks during atmospheric re-entry from LEO , 2017 .

[21]  E. Farahvashi,et al.  Methods to Reduce Uncertainties in Spacecraft Vulnerability Predictions , 2017 .

[22]  T. Lips,et al.  Scarab -a Multi-Disciplinary Code for Destruction Analysis of Space-Craft during Re-Entry , 2005 .

[23]  J. Grey Space propulsion. , 1996, Science.

[24]  Hugh G. Lewis,et al.  Demisability and survivability multi-objective optimisation for preliminary spacecraft design , 2017 .

[25]  Camilla Colombo,et al.  Survivability and demise criteria for sustainable spacecraft design , 2015 .

[26]  Shannon Ryan,et al.  A ballistic limit analysis programme for shielding against micrometeoroids and orbital debris , 2011 .

[27]  T. Lips,et al.  A comparison of commonly used re-entry analysis tools , 2005 .

[28]  P. Wallace The Union of Concerned Scientists , 2008 .

[29]  王东东,et al.  Computer Methods in Applied Mechanics and Engineering , 2004 .