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Commercial cloud computing in space

The ESA Open Space Innovation Platform Campaign for Cognitive Cloud Computing in Space (3CS) called for project proposals for the use of edge and cloud computing technologies in space. D-Orbit created a consortium including UniBap and Trillium to respond to this opportunity with a proposal to engage the cloud computing community to identify and fly applications on the ION SCV-004 mission.

United Kingdom

EISI_I-2022-00373

D-orbit
MOSFET Commercial plastic components survey and its SEE characterization

The aim of this activity is to:

Spain

20-D-S-TEC-05-e

ALTER TECHNOLOGY TUV...
Data compression as a service

The Data Compression as a Service (DCaaS) study aimed to bring the benefits of data compression to the experimenters on ESA's OPS-SAT platform. It focused on using the POCKET+ algorithm for the compression of housekeeping telemetry data. The project contained a space component, which performed the compression of provided user data, and a ground component, for the decompression of transmitted user data. Three use cases were selected within the scope of the project: file-to-file, packet-to-packet, and stream-to-stream lossless data transfers.

Germany

21-D-S-OPS-02-d

VisionSpace Technologies
A Comparative Study Of High-Level And Low-Level Implementations Of Deep Learning Models For Spacecraft

In this activity, Mission Control Space Services deployed a low-level implementation of the OPS-SAT SmartCam model using a Field Programmable Gate Array (FPGA), comparing against a high-level CPU model using Tensorflow Lite. Experiments showed that the FPGA implementation reproduced the precision and accuracy of the high-level model, while running at a slower speed. Further optimisations of the FPGA are expected to close the gap in timing and unlock new methods for deploying deep learning on spacecraft.

Canada

21-D-S-OPS-02-e

Mission Control Space...
AN AI-BASED SYSTEM FOR AN ACTIVE TRACKING OF EARTH FEATURES FROM OPS-SAT

In this activity, a proof of concept of an attitude control system based on artificial intelligence, as an alternative to current state-of-the-art systems based on model approaches, was developed and tested in a simulator and in the engineering model of ESA's OPS-SAT.

Spain

21-D-S-OPS-02-i

Adatica Engineering
MoBaTe – Enabling Model-Based Testing and Automated Test Case Generation for Ground Segment Data Systems

The driver behind the MoBaTe activity was to propose ways to improve the current software development and validation lifecycle using MBSE techniques to shift some of the system validation activities to the early stages of development. The roadmap to achieve this included identifying strategies, required model properties, modelling tools and languages needed to move from a requirements-based approach to a model-based approach. All this considering existing and established workflows and tools currently used by ESA.

Germany

21-D-T-OPS-01

Etamax Space GmbH
On-Board Anomaly Detection From The Ops-Sat Telemetry Using Deep Learning

Detecting anomalies from satellite telemetry is critical for the safe operation of that satellite. Although many approaches to autonomous onboard anomaly detection have already been proposed, most of them have so far only been tested on non-satellite or simulated data. This activity tackled this research gap and proposed an end-to-end machine learning-powered approach for detecting abnormal events in real-life OPS-SAT telemetry data, and deployed it on board a satellite.

Poland

21-D-S-OPS-02-f

KP Labs
Modular micropump fluidic systems: For system requiring ultrareliability, high performance and a compact design

Due to the ongoing miniaturisation and increased performance of electronics devices, alternative cooling methods are required, specifically mechanical pumping loops (MPL). Passive two-phase loops are not capable of cooling ESA's expected power densities up to 300 W/m2, so pumped two-phase loops are forecasted to replace their passive counterparts. According to Lapensée et al., “the most important component of a MPL is the pump and a pump failure directly results in MPL system failure, a reliable pump is therefore of vital importance". Wits et al.

Ireland

ETD 2020-07-c

University of Limerick
Integration of the COMPASS and TASTE toolsets (COMPASTA)

COMPASS is a tool for model-based system/software co-engineering developed in a series of ESA studies (2008–2016). It is based on a dialect of AADL and it offers a complete set of functionalities for formal verification, including requirements specification and analysis, contract-based design and verification, functional verification, fault specification, fault injection and RAMS analyses, including Fault Tree Analysis (FTA), Failure Modes and Effects Analysis (FMEA), Diagnosability Analysis, Fault Detection, Isolation and Recovery Analysis (FDIR).

Italy

20-D-T-TEC-04-i

Fondazione Bruno Kessler
R2D2 (Reliable Robust Dust Deflecting) Plug and Socket

To develop large-scale infrastructure on the Moon, many different systems will have to be shipped to the Moon to produce the necessary components. This means that the traditional design of systems cannot be assumed and a production machine cannot be expected to provide its own power especially when power demand is in the 100 kW – 1 MW range.

Luxembourg

20-D-T-TEC-03-e

MAANA Electric

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