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The “SaaSy ML” idea will provide experimenters with on-board Machine Learning (ML) functionalities that any app can subscribe to via a Software as a Service (SaaS) app hosted on the Satellite Experimental Processing Platform (SEPP). The ML features provided by the SaaS app will cover both training and prediction operations. The JSAT open-source java library for ML will be re-used thus making accessible over 100 training algorithms on-board a flying mission. Re-using the JSAT library will ensure the development to focus on the idea's novel aspect: a spacecraft SaaS app for in-orbit ML.

The MBSE and Space to Ground ICD activity started with the goal of applying MBSE practices to the preparation of the Space to Ground ICD (S2GICD). This study involves the following main steps:

The main objectives of this project were to develop a thruster prototype based on magnetic powder electrostatic propulsion and to test it in vacuum with direct thrust measurements. The aim was to check the robustness of the concept and to measure and calculate important performance parameters such as thrust and specific impulse, to allow a comparison with other thruster technologies. This project demonstrated for the first time the feasibility of electrostatic propulsion based on powder emission.

A GSTP De-Risk Framework with RUAG Space Germany designed and demonstrated a novel, compact and robust sensor head for angular sensors for space mechanisms, using modern and advanced materials and manufacturing methods.

The final performance tests provided evidence in terms of high precision manufacturability of ceramic packages.

The robust design was found to be suitable for the harsh space environment