Spherene AG

Spherene AG is a swiss software development startup providing technology to seamlessly integrate autonomous design into existing additive manufacturing workflows. Spherene AG is committed to the creation of a sustainable economy which is founded on the local manufacturing of only the objects that are needed. Its key principles are material-efficient 3D printing, upgrading, and repairing, instead of replacing & recycling or disposal.

The Integrated MBSE Analytics Platform (IMAP) has been developed in the course of the OSIP [OSIP] MBSE campaign’s MBSE2DataLake project. It demonstrates how MBSE data can be downstreamed from early phases and integrated with Telemetry data or system operations data. Applying MachineLearning analytics and customized visualization on these sets of integrated data provides seamless analysis capabilities and data browsing experience for the user. The approach leads to linking the former separated domains of System Design and AIT/Operations.

There is an urgent need to assess the levels of plastic pollution in the ocean, to allow for future monitoring and determine the efficacy of any remediation put into force. As a consequence, parallel to in situ observations, there is a growing interest in detecting marine debris using remote sensing satellite and UAV imagery. The Marine Remote Sensing Group (MRSG) at the University of the Aegean is one of the few groups worldwide with in-deep experience in developing artificial plastic debris target structures, in different configurations and polymer composition.

Optical high-resolution payloads require very high structural and thermal stability to work at their top performance. Performing a thermal analysis and being able to perform De-Risk activities is surely critical for what concerns optical payloads which is a highly competitive market.

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:

This activity investigates how mega-constellations can be used to provide low-Earth orbit (LEO) spacecraft with broadband low-latency services, a novel Concept with potential to disrupt spacecraft design, operation, and performance by allowing spacecraft to access mega-constellations’ enormous resources (Tbit/s throughputs) and global coverage at a lower cost than traditional data relay systems and ground station networks (two to fifty times cheaper, that is, a few hundred to a few thousand dollars per month for a daily net capacity from hundredths of Gbit up to almost ten Tbit).

Institut für Textiltechnik der RWTH Aachen University (ITA) and Institute for Structural Mechanics and Lightweight Design RWTH Aachen University (SLA) have already spun MoonFibres from regolith simulant. Gradel SARL uses the xFKin3D technological process to produces ultra-lightweight structural components made of various types of fibres and resin. This technology requires less material to create parts with equal structural strength as the ones produced in traditional ways. The produced parts can be 2D or 3D parts.

In order for off-Earth top surface structures built from regolith to protect astronauts from radiation, they need to be several metres thick. With support from European Space Agency (ESA) and Vertico, the Technical University Delft (TUD) advanced research into constructing habitats in empty lava tubes on Mars in order to create subsurface habitats. By building below ground level not only natural protection from radiation is achieved but also thermal insulation because the temperature below ground is more stable.

Remote detection and mapping of floating marine plastic litter (FMPL) from space needs to operate in synergy with clean up actions. This implicates that an observation system is needed combining high revisit and high spatial resolution. Currently there is no single remote sensing technology with sufficient revisit capabilities and spatial/spectral resolution relevant to FMPL dynamics. Therefore a combination of small drones, satellites and High Altitude Pseudo-Satellite (HAPS) is anticipated to provide the long term sustainable technical solution.

The project “Novel estimation of shallow water bathymetry using ICESat-2 laser altimetry, signal processing and machine learning and Sentinel-2 optical data in a highly automated approach” was funded under the European Space Agencies’ Open Space Innovation Platform (OSIP). The overall objective was to build a self-calibrating and efficient bathymetry mapping system by leveraging accurate and consistent ICESat-2 laser altimeter data as a calibration source for high-resolution Copernicus Sentinel-2 based water depth retrievals.