Advancing Spaceflight through a Digital Mirror and Artificial Intelligence
Human spaceflight represents a vital part of modern space exploration. The Artemis program and planned Gateway space station will soon push the boundaries of classical space exploration, necessitating innovative solutions to overcome the novel challenges of Life Support System (LSS) operation in extraterrestrial environments. Advanced simulation tools can facilitate the development and testing of LSSs within an environment that closely resembles actual mission conditions. This work presents the current development progress on a virtual model of the Columbus Science Laboratory onboard the International Space Station, specifically focusing on the Environmental Control and Life Support System as well as the Thermal Control System. The model was created using the simulation tool V-HAB (Virtual Habitat) and by performing a parameter identification study for the Condensing Heat Exchanger configuration. An initial test successfully demonstrated the methodology and enabled future development of a high-fidelity model. Additionally, the potential of integrating Machine Learning (ML) models for time series prediction was explored. The application of ML methods enables predictive maintenance, optimized resource allocation and enhanced system resilience, ultimately supporting the development of more efficient and reliable technologies.