The general goal of this project is to operationalize and deepen the findings and conclusions of the initial project “Exploring AI capabilities to support the evaluation process of ideas submitted in the OSIP platform.” which demonstrated that AI techniques and software (COGITO Discover) could be used positively to enhance and ease the evaluation of ideas, by providing some new indicators such as idea novelty (scoring 0-100) based on the notion of similarity between ideas and innovation projects.

The OPS-SAT MBSE activity had the 3 main objectives:

“Remote Sensing for Marine Litter - RESMALI” has identified the ideal parameters to study marine litter (ML) from space, including spectral bands with affordable signal-to-noise ratio (SNR) at top-of-atmosphere (TOA) level, in a range of wavelengths from visible to SWIR. To continue this path towards a dedicated mission, performance assessment against simulated real-case scenarios of ML is key. We want to build a simulator to estimate ML signal at TOA from a set of scenarios representing the various applications already targeted by the community (e.g.

Space system engineering is a complex activity, spanning multiple phases and involving different stakeholders using a variety of engineering approaches and tools. ESA has been investing in Model-Based System Engineering (MBSE) research for many years, developing different MBSE frameworks and Domain Specific Tools (DSTs). Recently, a broader need has been recognized to focus the MBSE efforts on semantic interoperability and associated model integration.

The main objective of the ELMASAT study was to brint into Capella the means to calculate the availability of a satellite system and provide extra facilities for trade-off analysis. As an example of application, an assesment of SEE detection and mitigation strategies was performed with respect to availability objectives.

The main objective of the project is the reverse engineering of the OPS-SAT system, creating a model of the existing system design. The model aims to be built in a way that it is most useful for OPS-SAT engineers to understand and discuss the existing design and use this as a basis for further development of the OPS-SAT system.

Model based approaches have proved to be efficient in supporting engineering activities, models replacing traditional document-based approaches. Nevertheless even in most advanced deployments, a lot of engineering artifacts are textual either because the return on investment of introducing models is too low on this particular case or because the information is more efficiently expressed in natural language even if consistency and correctness issues appears.