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The satellite AGILE (Astro-rivelatore Gamma a Immagini LEggero, “Light Gamma Ray Imaging Detector”) is a promising instrument for near-earth space research of the Italian Space(ASI) during the years 2007-2009: its scientific instrumentation has optimal imaging capabilities in both the gamma-ray energy range (30 MeV - 30 GeV) and hard X-ray range (15 - 45 keV). It will study the phenomena occurring in the high energy spectrum, such as: Active Galactic Nuclei, Gamma Ray Bursts, Gamma-ray Galactic Diffuse Emission, and more. The satellite was designed and built in years 2004-2006; this paper describes the design of the thermal control system of the satellite, with a survey of the flight prediction. As an example of uncertainty reduction, MLI performance characterization by test was done in an early phase of the AIV phase (i.e. well before the system level test), to meet stringent payload requirements in terms of temperature gradients and temperature stability.

The Alpha Magnetic Spectrometer (AMS-02) is a particle physics detector designed to be installed on the International Space Station for at least 3 years, in order to measure charged cosmic rays, and to search for dark matter, missing matter and antimatter. The silicon Tracker is the centre of AMS. It measures particle trajectories through AMS-02 strong magnetic field with a micron accuracy. The heat dissipated by the whole experiment is rejected to deep space by means of four radiators [4–5]: the two Tracker radiators assure the heat dissipation for the above mentioned silicon Tracker, and the two Main radiators reject to space all the heat dissipated by the power, command and control units. The four radiators have been designed, analyzed by means of detailed thermal mathematical models and finally constructed and tested. This paper focuses on the thermal mathematical models tuning to best fit the provided test data.

This paper reports on an automated technique for reducing lumped-parameter thermal models. The method is applied in case of a simple geometry (a flat radiator panel), first in steady state conditions and then a comparison in time-variable environment is carried on, assessing how the reduction procedure affects the effective thermal mass of the radiator. More complicated shapes are studied, including concave corners and holes. The technique is implemented by a Matlab® code and it is applied to reduce the heat-pipes- embedded-radiator model of AMS-02, an ISS external payload. The detailed and reduced models behaviour is simulated by SINDA® and the results are compared: existing specification for test-model correlation, regression line and histograms are used for the verification. Furthermore radiator functioning extreme situations are simulated to see the method validity limits in steady state, introducing the concept of ‘working volume’.