Nebula Public Library

Space weather observations and the prediction of expected disturbances on ground- and space-based infrastructure are critical for the safety and evolution of our modern society. Space weather events, like solar storms, can have a significant impact on navigation, communication, power grids and other electrical conducting infrastructures. Therefore, space weather predictions are very important, but recently lack a reliable estimation of the geo-effectivity as well as detailed information for regions and systems potentially affected.

In applications such as space traffic and disaster response management, there are growing public and private capabilities. Multiple different stakeholders can detect and identify events (space collision predictions, natural disaster definitions). Augmentation of events definitions lead to confusion for local authorities, operators or any users of these information for costly decisions. This project, Space DAO, sets the base infrastructure to agree on consensus mechanisms to reduce confusion and augment trust in key decision making information.

The market for life‐extension services for GEO satellites is expected to remain healthy over the foreseeable future: over the last 20 years, an average of 22 new GEO satellites have been launched per year. In total, ClearSpace expects there will be 370 potential Client satellites that will reach their end of life due to the limited fuel they have remaining over the 2026‐2041 period. ClearSpace believes a strong market penetration rate is feasible, as more than 30% of all the potential satellites belong to just 7 satellite operators.

For long-term studies, numerical simulations are at the center of predicting the space debris environment of the upcoming decades. In the scope of the study, the authors present the architecture and proof-of-concept results for a numerical simulation capable of modeling the long-term debris evolution over decades with a deterministic conjunction tracking model in contrast to typically employed Monte Carlo methods. For the simulation, an efficient propagator in modern C++ accounting for Earth’s gravitational anomalies, solar radiation pressure, and atmospheric drag was developed.