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A Heat Switch has been developed, namely a device able to autonomously regulate its own thermal conductance in function of the equipment dissipation and environmental heat sink conditions. It is based on a Loop Heat Pipe (LHP) technology, with a passive bypass valve which diverts the flow to the Compensation Chamber when needed for regulation purposes. The target application is the potential use on a Mars Rover thermal control system. The paper recalls the Heat Switch design, and reports the results of an extensive test campaign on the ground demonstrator. The performance of the device was found extremely satisfying, and often exceeded the system requirements.

In the paper some methods are presented, with the corresponding practical examples, related to MonteCarlo (MC) techniques for thermal model/test correlation purposes. The MonteCarlo techniques applied to model correlation are intended to be used as an alternative to empirical ‘manual’ correlation techniques, gradients methods, matrix methods based on least square fit minimization. First of all, Design Of Experiments (DoE) tools are used to determine the model response to uncertain parameters and the confidence level of such a response. A sensitivity map is built, allowing the design of the test to maximize the response of the system to the uncertain parameters. Techniques derived from the extreme statistics are used to extrapolate data beyond test limits, with a sufficient confidence in the queue behaviour.

Improvements on the thermal analysis for system perturbed by micro-thermal fluctuations are presented: the method applies to any kind of (small) perturbation, in particular to the random ones. Opposite to time domain conventional transient analysis, this method answers the need for frequency domain thermal analysis dictated by the newest scientific missions, with tight temperature stability requirements (expressed in the frequency domain). The small temperature fluctuations allow for assuming any thermal systems a linear one; hence linear system theory holds, and powerful tools to calculate key parameters like frequency response can be successfully employed. MIMO (Multi-Input-Multi-Output) systems theory is applied, the inputs being perturbations to the thermal system (boundary temperatures oscillations and power sources ripple of any shape: pulse, step, periodic, random, …), while the outputs are the temperatures of the sensible parts.