Modeling Crew Performance Degradation Due To Radiation Exposure In Space
The tools currently used to model risk prediction and degradation have a large margin of uncertainty due to a lack of human epidemiology data. Few people have been in space, and even fewer have been beyond LEO, resulting in a very limited data set for radiation exposure. In order to conduct statistically significant research those scenarios have been extrapolated beyond what�s reasonable. Earth-based analogs provide more data, but there are open questions about the scalability of their results. The objective of this doctoral research is to approach space radiation effects on human spaceflight from an engineering perspective by focusing on predicting performance degradation. This takes into account the physiological degradation that occurs to the central nervous system (CNS) as well as behavioral changes, but this research does not attempt to produce a risk prediction model based on biological data.
A framework has been created to anchor the development of a quantitative model suitable for estimating crew performance degradation due to radiation in space. Each path in the framework requires a separate transfer function to move to the next stage of the model and describes the effects of radiation exposure on human physiology. The framework accounts for potential physical changes, physical reaction or symptoms, and emotional or psychological reactions. These reactions connect to performance degradation characterized by changes in results to performance tests, attention allocation, information processing, etc. The next stages of research will involve performing a task analysis to narrow �performance� into specific metrics. A model based on the concepts of Bayesian Networks and probability risk assessments will be built using the results of the task analysis, allowing for measurable metrics of performance. This will establish a threshold for acceptable performance from which an assessment can be made to determine the degree of degraded performance.
James Nabity, University of Colorado, Boulder
ICES513: Computational Modeling for Human Health and Performance Analysis
The 50th International Conference on Environmental Systems was held virtually on 12 July 2021 through 14 July 2021.