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HabSim: Architecture for modelling disruptions, propagation, detection and repair in deep space habitats (2506.08903v1)

Published 10 Jun 2025 in eess.SY and cs.SY

Abstract: Establishing long-term human settlements in deep space presents significant challenges. Harsh environmental conditions, such as extreme temperature fluctuations, micrometeorite impacts, seismic activity, and exposure to solar and cosmic radiation pose obstacles to the design and operation of habitat systems. Prolonged mission duration and the vast distances from Earth introduce further complications in the form of delayed communication and limited resources, making autonomy especially desirable. Enabling simulation of the consequences of disruptions and their propagation through the various habitat subsystems is important for the development of autonomous and resilient space habitats. While existing simulation tools can assist in modeling some of these aspects, the integration of damage propagation, detection and repair in a computational model is rarely considered. This paper introduces and demonstrates a simulation architecture designed to model these aspects efficiently. By combining physics-based and phenomenological models, our approach balances computational efficiency with model fidelity. Furthermore, by coordinating subsystems operating at different time scales, we achieve real-time simulation capabilities. After describing the architecture, we demonstrate its application within HabSim, a space habitat system model developed by the NASA-funded Resilient Extraterrestrial Habitat Institute (RETHi). In these scenarios we consider fire hazard propagation within a lunar habitat to illustrate both how our architecture supports the modeling of disruption propagation, detection, and repair in a simulation environment and how the HabSim model can be leveraged for through stochastic simulations to support resilience assessment. The architecture developed herein is efficient and scalable, enabling researchers to gain insight into resilience, autonomy and decision-making.

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