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How to efficiently integrate thermal space analysis models?

Written by Team Nitrexo | Sep 13, 2022 9:31:42 AM

Too many errors and time lost

We spoke to stakeholders in the space industry about how to transfer and integrate space thermal analysis models in a more efficient way. At present, a huge bottleneck lies in the creation of reduced thermal models and their transfer from subcontractors to prime contractors, for each iteration. Although, new methods to facilitate the transfer and integration of thermal models are starting to emerge such as surrogate models, co-simulation, etc…

The classical approach to reduce thermal models is still widely used and mostly performed “manually” by the space thermal engineers' community. It is very time-consuming, prone to errors and dependent on the user. 

Methods, but no standard ones

A lot of methods to create reduced thermal models from detailed thermal models have been implemented so far in different fields. However, there is still no standard method globally available for the whole space thermal engineers' community as such. 

Finding a needle in a haystack

You group the nodes of the same part, part by part, with similar temperatures, with same material properties, in the detailed thermal models, for the worst hot and cold steady state analysis cases. Then, the geometries associated to these quasi-isothermal nodes are redefined to match with the reduced thermal model nodal breakdown to limit the number of surfaces. These latter nodes are merged into single nodes within the reduced thermal models.

The physical properties of the detailed thermal model nodes that are being merged into single nodes such as thermal capacitances as well as the thermal loads, linear conductors and radiative couplings are summed up and assigned to the condensed nodes accordingly. Then, the reduced thermal model is correlated according to the European Cooperation for Space Standardization (ECSS) requirements. That means analysing the reduced thermal model nodes that do not meet the ECSS requirements and calculating the relevant positive optimised thermal conductive couplings to get the targeted average temperatures and heat fluxes of group of detailed thermal model nodes. Today, this process is widely used and mostly performed “manually” by the space thermal engineers' community. 

Results

Benefits: Keeping the physical properties of the Thermal Mathematical Model (TMM) (no artificial conductors) and the Reduced Geometrical Mathematical Model (RGMM) can be integrated into another thermal model. 

Limitations: Built on user-defined basis, time-consuming and error-prone. 

Why it matters

Standardizing the thermal model reduction process will reduce both time and computing, which affect the product development budget, as well as the risk. 

How can the digital engineer assist you?


 We will standardize and fully automate this process, and make it accessible to the entire space thermal engineers’ community for free via the web at Digital Engineer®