Spacecraft thermal design with the Generalized Extremal Optimization Algorithm

Abstract

This article describes an application of the Generalized Extremal Optimization (GEO) algorithm to the inverse design of a spacecraft thermal control system. GEO is a recently proposed global search meta-heuristic (Sousa, F.L. and Ramos, F.M., 2002, Function optimization using extremal dynamics. In: Proceedings of the 4th International Conference on Inverse Problems in Engineering (cd-rom), Rio de Janeiro, Brazil.; Sousa, F.L., Ramos, F.M., Paglione, P. and Girardi, R.M., 2003, New stochastic algorithm for design optimization. AIAA Journal, 41(9), 1808–1818.; Sousa, F.L., Ramos, F.M., Galski, R.L. and Muraoka, I., 2005, Chapter III. In: L.N. De Castro and F.J. Von Zuben (Eds) Generalized Extremal Optimization: A New Meta-heuristic Inspired by a Model of Natural Evolution, Accepted for publication in Recent Developments in Biologically Inspired Computing (Hershey, PA: Idea Group Inc.).) based on a model of natural evolution (Bak, P. and Sneppen, K., 1993, Punctuated equilibrium and criticality in a simple model of evolution. Physical Review Letters, 71(24), 4083–4086), and specially devised to be used in complex optimization problems (Sousa, F.L., Vlassov, V. and Ramos, F.M., 2002, Heat pipe design through generalized extremal optimization. In: Proceedings of the IX Brazilian Congress of Engineering and Thermal Sciences – ENCIT 2002, Caxambu, MG, Brazil.). GEO is easy to implement, has only one free parameter to adjust, does not make use of derivatives and can be applied to constrained or unconstrained problems, and to non-convex or even disjoint design spaces with any combination of continuous, discrete, or integer variables. The application reported here concerns the optimum design of a simplified configuration of the Brazilian Multi-mission Platform (in Portuguese, Plataforma Multi-missão, PMM) thermal control subsystem, comprising five radiators and one battery heater. The PMM is a multi-purpose space platform to be used in different types of missions such as Earth observation, scientific, or meteorological data collecting. The design procedure is tackled as a multiobjective optimization problem, considering two critical cases, operational hot case (HC) and cold case (CC). The results indicate the existence of non-intuitive, new and more efficient design solutions.