49th International Conference on Environmental Systems ICES-2019-367 7-11 July 2019, Boston, Massachusetts

CRaTER Observations from Lunar Orbit of the Galactic Cosmic Radiation Environment Through the Complete 24

Wouter C. de Wet1 and Fatemeh Rahmanifard2 and Nathan A. Schwadron3and Harlan E. Spence4 University of New Hampshire, Durham, NH, 03824

and

Lawrence W. Townsend5 University of Tennessee, Knoxville, TN, 37996

Galactic cosmic radiation (GCR) presents a unique challenge to extended human exploration operations in the deep space environment. This challenge involves understanding and mitigating the biological risk associated with the ionizing radiation doses received by crew in flight. As such, an accurate understanding of the deep space GCR environment is an important part of the mission planning process. In this work, we present a comparison of the primary GCR conditions observed by the Cosmic Ray Telescope for the Effects of Radiation (CRaTER) instrument in lunar orbit to the conditions predicted by the Matthia 2013 model on NASA’s On-Line Tool for the Assessment of Radiation in Space during Cycle 24. The CRaTER instrument aboard the Lunar Reconnaissance Orbiter began actively observing the lunar radiation environment soon after it launched in June 2009. Still in operation today, CRaTER has observed the dose rates associated with the primary GCR environment for a time period spanning over a complete solar cycle. This is significant, as it provides the opportunity to perform a comprehensive evaluation of current GCR models using observations made in free space conditions over a wide range of solar activity. Parameterizations, such as the one found in the Matthia 2013 model, are often used to define GCR conditions as a function of time and/or solar activity. The expected response of the CRaTER instrument to a predefined set of GCR conditions according to the Matthia 2013 model is obtained using Monte Carlo radiation transport methods. This expected response curve, calculated using the MCNP6 charged particle transport code, is used to extract free space GCR conditions from the dose rates observed by the CRaTER instrument over time. A discussion of the differences between the observed and predicted GCR flux timeseries is presented.

Nomenclature CRaTER = Cosmic Ray Telescope for the Effects of Radiation GCR = Galactic Cosmic Radiation ISSN = International Number LET = Linear Energy Transfer LRO = Lunar Reconnaissance Orbiter MCNP6 = Monte Carlo N-Particle 6 OLTARIS = On-Line Tool for the Assessment of Radiation in Space TEP = Tissue-Equivalent Plastic W = Wolf Number

1 Research Scientist, Institute for the Study of Earth, Oceans, and Space, 8 College Road, Durham, NH, 03824. 2 Graduate Research Ass., Institute for the Study of Earth, Oceans, and Space, 8 College Road, Durham, NH, 03824. 3 Professor, Institute for the Study of Earth, Oceans, and Space, 8 College Road, Durham, NH, 03824. 4 Director, Institute for the Study of Earth, Oceans, and Space, 8 College Road, Durham, NH, 03824. 5 Professor, Department of Nuclear Engineering, 1412 Circle Drive, Knoxville, TN, 37996.

Copyright © 2019 Wouter C. de Wet I. Introduction HE high-energy and heavy charged particle component of the interplanetary extraterrestrial radiation environment is dominated by two sources. The first, and most proximal, source of this radiation is the . Solar energetic T particles (SEP) are often associated with coronal mass ejections and consist primarily of H and He isotopes– although elements as heavy as Fe are also included in observable quantities. SEP events are infrequent and can last anywhere from hours to days for any particular location within the . The second source of interplanetary radiation lies far beyond the outer limits of the heliosphere. This source, which may be more appropriately described as an ensemble of sources, is commonly referred to as galactic cosmic radiation (GCR) in literature.1, 2, 3 Unlike the relatively infrequent high-fluence solar energetic particle radiation, galactic cosmic radiation is consistent over long periods of time. The primary GCR spectrum consists of all elements from H through Fe in significant quantities over many generations of energy ranging from keV to hundreds of GeV. The most abundant energy of GCR particles is on the order of hundreds of A MeV.4,5 The GCR fluence rate, or flux, is generally much smaller than the flux of an average SEP event. Although the sun is only directly responsible for the intermittent releases of SEP particles, solar activity significantly influences the GCR spectrum over the 11-year solar cycle.2,6 During , which is the period of highest solar activity, the GCR spectrum is modulated more strongly than during . In this work, is defined as the period beginning in mid-2009 and ending mid-2018. There are various models throughout literature that describe the behavior of the GCR spectrum as a function of solar activity and time. The Matthia 2013 model described in Ref. 7 uses a single parameter W, called the Wolf number, to describe the GCR modulation conditions. The Wolf number, also commonly referred to as international sunspot number, is based on the mean sunspot number and ranges from 0 to 269. Large values of W number indicate high solar activity, which results in reduction of the GCR flux. A single value of W is used to entirely describe a specific GCR condition, including both energy and isotopic abundance. Therefore, the free-space GCR environment for any given month can be accurately approximated given the observed mean value of W for that period– excluding times in which an active SEP event is occurring. Similarly, if the entire GCR condition for a given period of time is explicitly known, it follows that the mean Wolf number corresponding to that period can, theoretically, be obtained retroactively using that data. However, observing the entire GCR condition is less straightforward than observing Wolf number. Therefore, validation of the Matthia 2013 model is performed by comparing the model results with specific species-energy flux in-situ observations, such as the Advanced Composition Explorer (ACE) spacecraft, or other relative data such as neutron monitor count rates. The Cosmic Ray Telescope for the Effects of Radiation (CRaTER) instrument has been in operation since the launch of the Lunar Reconnaissance Orbiter in June 2009. The instrument consists of six cylindrical Si solid-state heavy charged particle detectors.8 Three of the six detectors are thin detectors and the other three are thick detectors. The thin detectors have an axial thickness of roughly 149 µm, while the thick detectors have an axial Accepted thickness of roughly 1.0 mm. The detectors are arranged into a cylindrical telescope as three individual pairs separated by two cylindrical volumes of tissue-equivalent Al D1 plastic (TEP). Each detector pair consists of one thin D2 detector followed by one thick detector. The detectors are

TEP 1 named D1-D6 according to the order of their appearance in the detector stack. The thin detectors named D1, D3, D3 and D5 while the thick detectors are named D2, D4, and D4 D6. All components of the telescope stack share a TEP 2 common cylindrical axis and each end of the telescope is D5 D6 covered by a thin layer of aluminum. See Figure 1 for a Al simplified illustration of the CRaTER telescope geometry. CRaTER is designed to operate as a linear Rejected energy transfer (LET) spectrometer. The combination of thin and thick detectors allows each pair to cover all 8 Figure 1. CRaTER Instrument Geometry. A two- values of LET between 0.09 keV/µm and 2.2 MeV/µm. dimensional geometrical representation of the This unique design enables users to quantify how the CRaTER telescope with the respective accepted and primary GCR spectrum changes as a function of distance rejected incident particle angles labeled. through the human body. For more information about the

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CRaTER instrument, see Ref. 8. In this work, the expected response of the 10-3 CRaTER instrument to a predefined set of GCR conditions according to the Matthia 2013 model is calculated. This response function is used to extract free space GCR conditions from the dose rates observed by the CRaTER instrument over solar cycle 24.

II. CRaTER Response Modeling Dose Rate, cGy/day Rate, Dose A characterization of the relationship between all possible GCR boundary conditions and their resulting expected 10-4 CRaTER observations is necessary to extract GCR conditions from observations made by the CRaTER instrument. This 0 20 40 60 80 100 120 140 160 180 200 process begins with isolating a data Wolf Number product from CRaTER observations that Figure 2. CRaTER Response Function. The absorbed dose rate serves as an effective measurement the in Si observed in the third detector pair (D5, D6) with a coincidence primary GCR spectrum and is also requirement in the first two (D1, D2 and D3, D4) detector pairs as reproducible using radiation transport a function of Wolf Number. These results were calculated using methods. After which comes gathering a MCNP6. The error bars represent uncertainty from Monte Carlo set of boundary conditions that is sufficient statistics. to cover the entire range of possible GCR conditions. The next step is to determine the instrument response for each boundary condition independently using the same radiation transport geometry. The results of the transport calculations are then used to assemble the response function. The final step is to use this response function to extract the GCR condition from observed data.

A. CRaTER Observations The CRaTER observation selected for response function modeling is the dose rate in the third detector pair (D5, D6). An additional requirement of coincidence in the first (D1, D2) and second (D3, D4) detector pairs constrains the detected particles to a 31.5° conical field of

# 10-4 view. The coincidence conditions applied 6 to the recorded dose rates are sufficient to 5.5 eliminate side-penetrating particles, as well as minimize the effects of the spacecraft 5 bulk. A further requirement is imposed on 4.5 the relative absorbed dose rates in each detector pair in order to identify only 4 particles that enter from the free-space end 3.5 of the telescope. This requirement is that the absorbed dose in the third pair must be 3

Dose Rate, cGy/day Rate, Dose greater than the absorbed dose in the 2.5 second pair. Furthermore, the absorbed dose in the second pair must also be greater 2 than the absorbed dose in the first pair. The 1.5 MCNP6/Matthia effective field of view is illustrated in Observed Figure 1. Previous modeling efforts 1 2008 2010 2012 2014 2016 2018 2020 demonstrate excellent agreement between Date, year CRaTER observations and the Figure 3. Cycle 24 Dose Rate. The absorbed dose rate in Si corresponding Monte Carlo radiation observed in the third detector pair (D5, D6) with a coincidence transport results for triple-coincident requirement in the first two (D1, D2 and D3, D4) detector pairs as particles entering the telescope from the a function of time for solar cycle 24. free space end.9

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B. Boundary Conditions

According to Ref. 10, the monthly 150 mean sunspot number is not expected to Observed surpass W=150 during solar cycle 24. Therefore, the maximum monthly averaged sunspot number considered in this study is W=200. A total of nine values 100 W = 0, 10, 25, 50, 75, 100, 125, 150, and 200 were selected to represent the entire range of possible GCR conditions. The free-space GCR flux for each value of W Wolf Number according to the Matthia 2013 model was 50 calculated using NASA Langley Research Center’s On-Line Tool for the Assessment of Radiation in Space (OLTARIS).11 The boundary condition GCR flux includes all elements from H to Ni with energies 0 2008 2010 2012 2014 2016 2018 2020 ranging from 100A keV to 10A GeV. Date, year

C. Radiation Transport Model Figure 4. Cycle 24 Wolf Number. The Wolf number as a function The MCNP6 Monte Carlo radiation of time for solar cycle 24. transport code is used to calculate the instrument response for each boundary condition individually.12 Incident GCR particles are sampled on a spherical shell surrounding the telescope. A zero-importance sheath surrounding the outside and bottom layer of the detector stack ensures that only particles from the region of interest enter the telescope. Furthermore, each coincidence and relative dose requirements discussed are also enforced. The absorbed dose in the third detector pair is tallied. Logic that prevents any individual particle from scoring in both the D5 and D6 tallies ensures that particles are not being double counted in order to maintain consistency with observed data processing.

D. Dose Response Function

The assembled absorbed dose response 150 function is illustrated in Figure 2. The Wo lf Number values calculated using MCNP6 are given 100 as data points with error bars. These error ffDi % . bars represent the statistical uncertainty 50 from the Monte Carlo calculation. The blue line connecting the data points is 0 calculated using an akimal spline. The 2008 2010 2012 2014 2016 2018 2020 CRaTER response function is smooth and monotonically decreasing with increasing 150 Wolf number, as expected. This response Do se function provides the ability to interpolate 100 the expected observed dose rate for any ffDi % . valid Wolf number. Conversely, this 50 response function may also be used to retroactively infer a Wolf number 0 2008 2010 2012 2014 2016 2018 2020 corresponding to a given observed dose Date, year rate. Figure 5. Relative Differences. The monthly percent difference III. Results between the modeled and observed results for a) the Wolf number (top) and b) the absorbed dose rate (bottom) as a function of time for The dose rate in the third detector pair solar cycle 24. for solar cycle 24 is illustrated in Figure 3. The observed data (black squares) are binned as monthly averages. The expected results (red circles) are the dose values interpolated from the response function using the monthly-averaged international sunspot number (ISSN) from the SILSO World Data Center.4 In Figure 4, international sunspot number (red circles) is plotted alongside the Wolf number inferred from the observed CRaTER dose rates (black squares) as a function of time for solar cycle 24. In 4 International Conference on Environmental Systems

both Figures 3 and 4, there is clear agreement between the expected and observed results. Figure 5 illustrates the monthly percent difference between the modeled and observed results in both Wolf number and dose rate as a function of time for solar cycle 24. The mean monthly percent difference between the modeled and observed results is 31.5% in Wolf number, and 18.1% in dose rate.

IV. Conclusion In conclusion, using the Matthia 2013 prescription for GCR condition to define a relationship between Wolf number and the dose rate observed by the CRaTER instrument is a viable method of retroactively extracting free space conditions. According to these results, however, the Matthia 2013 model in combination with the ISSN timeseries data appear to overpredict the dose rate during solar minimum, and underpredict the dose rate during solar maximum. Furthermore, the relatively high variance in monthly-averaged ISSN is not reflected in the CRaTER observation data. This indicates that sunspot number alone, while correct over long periods of time, may be insufficient to directly infer the GCR condition for shorter time periods. The authors plan to repeat this study using other GCR models as well.

Acknowledgments This work was performed under the auspices of NASA grant number NNG11PA03C.

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