Probabilistic Forecasting of Radiation Exposure for Spaceflight
This work addresses the health risk of radiation exposure for astronauts on missions to the Moon and Mars by providing predictive models to enhance decision-making, though it appears incremental as it builds on existing monitoring tools with new data integration.
The paper tackles the problem of forecasting radiation exposure for spaceflight beyond low-Earth orbit by developing a machine learning model using multimodal time-series data, including full-disk solar imagery for the first time, and demonstrates its ability to predict the onset and decay of solar proton events.
Extended human presence beyond low-Earth orbit (BLEO) during missions to the Moon and Mars will pose significant challenges in the near future. A primary health risk associated with these missions is radiation exposure, primarily from galatic cosmic rays (GCRs) and solar proton events (SPEs). While GCRs present a more consistent, albeit modulated threat, SPEs are harder to predict and can deliver acute doses over short periods. Currently NASA utilizes analytical tools for monitoring the space radiation environment in order to make decisions of immediate action to shelter astronauts. However this reactive approach could be significantly enhanced by predictive models that can forecast radiation exposure in advance, ideally hours ahead of major events, while providing estimates of prediction uncertainty to improve decision-making. In this work we present a machine learning approach for forecasting radiation exposure in BLEO using multimodal time-series data including direct solar imagery from Solar Dynamics Observatory, X-ray flux measurements from GOES missions, and radiation dose measurements from the BioSentinel satellite that was launched as part of Artemis~1 mission. To our knowledge, this is the first time full-disk solar imagery has been used to forecast radiation exposure. We demonstrate that our model can predict the onset of increased radiation due to an SPE event, as well as the radiation decay profile after an event has occurred.