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Galactic cosmic rays enter Earth's atmosphere after interacting with the geomagnetic field. The primary galactic cosmic rays spectrum is fundamentally changed as it interacts with Earth's atmosphere through nuclear and atomic interactions. At points deeper in the atmosphere, such as at airline altitudes, the radiation environment is a combination of the primary galactic cosmic rays and the secondary particles produced through nuclear interactions. The RaD-X balloon experiment measured the atmospheric radiation environment above 20 km during 2 days in September 2015. These experimental measurements were used to validate and quantify uncertainty in physics-based models used to calculate exposure levels for commercial aviation. In this paper, the Badhwar-O'Neill 2014, the International Organization for Standardization 15390, and the German Aerospace Company galactic cosmic ray environment models are used as input into the same radiation transport code to predict and compare dosimetric quantities to RaD-X measurements. In general, the various model results match the measured tissue equivalent dose well, with results generated by the German Aerospace Center galactic cosmic ray environment model providing the best comparison. For dose equivalent and dose measured in silicon, however, the models were compared less favorably to the measurements.

Accurate galactic cosmic ray (GCR) models are required to assess crew exposure during long-duration missions to the Moon or Mars. Many of these models have been developed and compared to available measurements, with uncertainty estimates usually stated to be less than 15%. However, when the models are evaluated over a common epoch and propagated through to effective dose, relative differences exceeding 50% are observed. This indicates that the metrics used to communicate GCR model uncertainty can be better tied to exposure quantities of interest for shielding applications. This is the first of three papers focused on addressing this need. In this work, the focus is on quantifying the extent to which each GCR ion and energy group, prior to entering any shielding material or body tissue, contributes to effective dose behind shielding. Results can be used to more accurately calibrate model-free parameters and provide a mechanism for refocusing validation efforts on measurements taken over important energy regions. Results can also be used as references to guide future nuclear cross-section measurements and radiobiology experiments. It is found that GCR with Z>2 and boundary energies below 500 MeV/n induce less than 5% of the total effective dose behind shielding. This finding is important given that most of the GCR models are developed and validated against Advanced Composition Explorer/Cosmic Ray Isotope Spectrometer (ACE/CRIS) measurements taken below 500 MeV/n. It is therefore possible for two models to very accurately reproduce the ACE/CRIS data while inducing very different effective dose values behind shielding.

This is the last of three papers focused on quantifying the uncertainty associated with galactic cosmic rays (GCR) models used for space radiation shielding applications. In the first paper, it was found that GCR ions with Z>2 and boundary energy below 500 MeV/nucleon induce less than 5% of the total effective dose behind shielding. This is an important finding since GCR model development and validation have been heavily biased toward Advanced Composition Explorer/Cosmic Ray Isotope Spectrometer measurements below 500 MeV/nucleon. Weights were also developed that quantify the relative contribution of defined GCR energy and charge groups to effective dose behind shielding. In the second paper, it was shown that these weights could be used to efficiently propagate GCR model uncertainties into effective dose behind shielding. In this work, uncertainties are quantified for a few commonly used GCR models. A validation metric is developed that accounts for measurements uncertainty, and the metric is coupled to the fast uncertainty propagation method. For this work, the Badhwar-O'Neill (BON) 2010 and 2011 and the Matthia GCR models are compared to an extensive measurement database. It is shown that BON2011 systematically overestimates heavy ion fluxes in the range 0.5-4 GeV/nucleon. The BON2010 and BON2011 also show moderate and large errors in reproducing past solar activity near the 2000 solar maximum and 2010 solar minimum. It is found that all three models induce relative errors in effective dose in the interval [-20%, 20%] at a 68% confidence level. The BON2010 and Matthia models are found to have similar overall uncertainty estimates and are preferred for space radiation shielding applications.

In order to assess the astronaut exposure received within vehicles or habitats, accurate models of the ambient galactic cosmic ray (GCR) environment are required. Many models have been developed and compared to measurements, with uncertainty estimates often stated to be within 15%. However, intercode comparisons can lead to differences in effective dose exceeding 50%. This is the second of three papers focused on resolving this discrepancy. The first paper showed that GCR heavy ions with boundary energies below 500 MeV/n induce less than 5% of the total effective dose behind shielding. Yet, due to limitations on available data, model development and validation are heavily influenced by comparisons to measurements taken below 500 MeV/n. In the current work, the focus is on developing an efficient method for propagating uncertainties in the ambient GCR environment to effective dose values behind shielding. A simple approach utilizing sensitivity results from the first paper is described and shown to be equivalent to a computationally expensive Monte Carlo uncertainty propagation. The simple approach allows a full uncertainty propagation to be performed once GCR uncertainty distributions are established. This rapid analysis capability may be integrated into broader probabilistic radiation shielding analysis and also allows error bars (representing boundary condition uncertainty) to be placed around point estimates of effective dose.