We describe a tool suite, CREME, which combines existing capabilities of CREME96 and CREME86 with new radiation environment models and new Monte Carlo computational capabilities for single event effects and total ionizing dose

Adams, James H., Jr.

Barghouty, Abdulnasser F.

Reed, Robert A.

Sierawski,  Brian D.

Watts, John W., Jr.

NASA Technical Reports Server

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Acknowledgements: 
This work was supported by the Autonomous Systems & Avionic Project of NASA’s ETDD Program. 
Additional support has been provided by the Defense Threat Reduction Agency Basic Research Program 
and the NASA Electronic Parts and Packaging Program. 
CRÈME: The 2011 Revision of the Cosmic Ray 
Effects on Micro-Electronics Code 
J. H. Adams, Jr., A. F. Barghouty, M. H. Mendenhall, R. A. Reed, B. D. Sierawski, J. W. Watts, Jr.,  
and R. A. Weller 
ABSTRACT: 
We describe a tool suite, CRÈME, which combines existing capabilities of CREME96 and 
CREME86 with new radiation environment models and new Monte Carlo computational capabilities 
for single event effects and total ionizing dose. 
Presenting Author: 
Robert A. Weller, Vanderbilt University, Department of Electrical Engineering and Computer Science, 
Nashville, TN. Email: robert.a.weller@vanderbilt.edu. Phone: (615) 343-6027 
 
Contributing Authors: 
James H. Adams, Jr., The University of Alabama, Huntsville, AL 
Abdulnasser F. Barghouty, NASA Marshall Space Flight Center, Hunstville, AL 
Marcus H. Mendenhall, Vanderbilt University, Department of Electrical Engineering and Computer 
Science, Nashville, TN  
Robert A. Reed, Vanderbilt University, Department of Electrical Engineering and Computer Science, 
Nashville, TN 
Brian D. Sierawski, Vanderbilt University, Institute for Space and Defense Electronics, Nashville, TN 
John W. Watts, Jr., Independent Consultant, Huntsville, AL  
 
Session Preference: Environments  
Presentation Preference: Poster 
 
https://ntrs.nasa.gov/search.jsp?R=20120015473 2019-08-30T22:43:54+00:00Z
 1
I.	Introduction	
The Cosmic Ray Effects on Microelectronics Code (CRÈME) was first released in 1986 [1]. 
Over the following ten years there were many advances in our understanding of the space 
radiation environment.  
During this period it was realized that galactic cosmic ray modulation had not only an eleven 
year cycle but also a twenty-two year cycle [2]. Furthermore it was recognized that the sunspot 
number is a leading indicator for galactic cosmic ray modulation and could be used to accurately 
model modulation [3]. Small 3He-rich events that were found to be enriched in heavy ions [4], 
accounting for much of the dispersion in elemental composition reported in CRÈME 86. It was 
discovered that solar energetic particles (SEPs) were accelerated in coronal mass ejections 
(CMEs) [5] and this was the source of the largest solar particle events (SPEs) [6]. New data 
[7],[8] made it possible to model the charge states of solar energetic particles. Also it was shown 
that rise in the single event upset (SEU) cross section could be described by an integral Weibull 
distribution [9]. All these and other revisions were included in CRÈME 96 [10]. 
A decade after the release of CRÈME96 it was becoming obvious that two segments of the site 
needed to be updated, selected environment models and rate prediction approaches. In this work, 
we describe the evaluation of environment models and their incorporation into the updated 
CRÈME web site. We used a chi-squared approach to evaluate three Galactic Cosmic Ray 
models (a fourth model will be evaluated in the final paper) and selected a single model for the 
new CRÈME site. We also developed a new model that describes the albedo neutron 
environment near the surface of the moon. Finally, for environments, this revision also includes a 
revised description of the transport of the space radiation environment through shielding. 
These issues prompted the revision of CREME96 that is described here.. The latest version of CRÈME, 
together with the two earlier versions, is now available at https://creme.isde.vanderbilt.edu/. 
II.	Environmental	Models	
II.a. Galactic Cosmic Ray Model: CREME96 used the Nymmik Model [3], which was adopted 
as a standard by the International Standards Organization (ISO). To choose a model for this 
revision, we reviewed the models that are available in the literature and chose those that modeled 
the differential energy spectra over the energy range from at least 10 MeV/u to 100 GeV/u. The 
models satisfying these requirements are the revised Nymmik Model [12], the CHIME Model 
[13], and the Badhwar-O’Neill Model [14]. 
We evaluated the Badhwar-O’Neill, CHIME and updated Nymmik models by comparing them 
with measured elemental spectra from an evaluated database we have developed. This database 
will contain more than 380 measurements of the elemental spectra of GCRs ranging from 
hydrogen to iron and from 10 MeV/u to 1 TeV/u. These measurements cover the time period 
from 1960 to the present. We have compared these individual evaluated spectra with each model 
by calculating the reduced chi-squared between each model and each spectrum, where reduced 
chi-squared is defined as:  
 2
1
2
2
)](11 ii
N
i i
Ef 



 
 2
Where  is the measured flux at Ei, i is the error in this measurement and f(Ei) is the flux 
calculated at Ei from the model under test.  is N-p-1 where N is the number of data points in the 
spectrum, p is the number of free parameters in the model under test and 2/ is the reduced chi-
squared. i is proportional to ඥ?? where ni is the number of detected cosmic rays used to 
construct i. Here we have bounded i to be 0.1i to account for systematic errors, especially in 
the determination of the geometrical factor of the instrument. The results are given in Table 1 
below. Based on these results we chose the Nymmik model for the revision. Since this evaluation 
was made, the Badhwar-O’Neill model has itself been revised [15]. We will evaluate this new 
model and report the results in the full paper to follow this summary. 
 
 
 
 
 
 
 
 
The CRÈME 2009 Nymmik model has an added advantage over other models. Because it uses 
the sunspot number as a proxy for modulation, it has some ability to predict the level of 
modulation up to a year in advance. This requires current data in the monthly smoothed sunspot 
number. These data are obtained periodically from the Solar Influences Data Center at the Royal 
Belgian Observatory (http://sidc.be/sunspot-data/). See Figure 1 for a comparison with CREME96. 
II.b. Lunar Neutron Albedo: We have added to 
CRÈME a model for the neutron albedo coming 
from the lunar surface due to cosmic rays 
bombarding the surface. This model is based on 
a GEANT4 calculation of the albedo from 
protons and helium nuclei striking the lunar 
surface. The GEANT4 neutron albedo flux 
calculations were conducted at discrete, 
logarithmically-spaced energies over the full 
energy range of the cosmic ray spectrum. The 
neutron albedo flux was then weighted to match 
the proton and helium spectra at the Moon 
calculated by CRÈME. The results of these 
calculations are compared with the neutron 
albedo measured on the Lunar Prospector 
mission in Figure 2. 
 
III.	New	Computational	Capabilities	
III.b. HZETRN 1995/NUCFRG2: We revisited the radiation transport code in CRÈME 96 [10] 
that is used to determine the radiation environment at the location of the part within the 
spacecraft for a given radiation environment at the surface of the spacecraft. CREME96 used a 
radiation transport code called UPROP [16] that was developed for transport of cosmic rays 
Model Name Badhwar-O’Neill Nymmik CHIME 
Hydrogen 3.45 1.28 1.37 
Helium 2.21 1.38 1.69 
Oxygen 0.71 1.21 0.65 
Iron 1.32 1.13 1.32 
Overall 2.46 1.31 1.46 
Table 1: The weighted 
mean results on the 
reduced chi-squared for 
all the spectral fits. The 
CRÈME 2009 Nymmik 
Model gives the best fits 
overall. 
100 101 102 103 104 105
Kinetic Energy (MeV/nucleon)
10-5
10-3
10-1
101
103
Fl
ux
 (m
2 -
s-
sr
-M
eV
/n
uc
)-1
1-H Creme-96
1-H Nymmik
Figure 1. A comparison of the proton flux predicted 
by CREME96 and CRÈME 2009.  Note the large 
difference for protons below 10 MeV, but the 
general agreement above 10 MeV. 
 3
through cosmic ray detectors and across interstellar space from the cosmic ray sources to Earth. 
UPROP was chosen because it solves the Boltzmann transport equation using a marching 
procedure and therefore is much faster than Monte Carlo codes. We compared [17] UPROP with 
HZETRN (the 1995 version) [18] and two Monte Carlo codes, FLUKA [19] and GEANT4 [20]. 
Our version of HZETRN was obtained from the NASA COSMIC software collection (currently 
at http://www.openchannelfoundation.org/cosmic/) in the late 1990s. 
HZETRN is a Boltzmann 
solver that also uses a 
marching procedure. Our 
results show that UPROP 
performed poorer than the 
other codes for protons and 
also for heavy ions at low 
energies. Unlike HZETRN, 
UPROP does not transport 
neutrons. This is a deficiency 
for evaluating radiation 
effects on the Moon or inside 
a massive spacecraft like the 
ISS. We found that HZETRN 
agreed reasonably well with 
the Monte Carlo codes except 
for neutrons at low energies. 
As a result of these comparisons we have chosen to include the 1995 version of HZETRN [17] as 
a users selectable option in the latest revision of CRÈME.  
	IV.	Conclusions	
Revised models for the CRÈME web site that provide improved fidelity and performance are 
described. The resulting web-based tool combines existing capabilities of CREME96 and 
CREME86 along with new Monte Carlo computational capabilities to support improved single 
event effects and total ionizing dose simulations. 
	V.	References:	
[1]  “Cosmic Ray Effects on Microelectronics, Part IV”, James H. Adams, Jr., NRL Memorandum 
Report 5901, December 31, 1986 (available at www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA176611) 
[2]  “Characteristics of the 22-Year Modulation of Cosmic Rays as Seen by Neutron Monitors”, W. R. 
Webber and J. A. Lockwood, JGR, 98, 8735-8740, (1988) 
[3]  “A Model of Galactic Cosmic Ray Fluxes”, R.A. Nymmik, M.I. Panasyuk, T.I. Pervaja, and A.A. 
Suslov, Nucl. Tracks Radiat. Meas. 20, 427 (1992).  
[4]  “The heavy-ion compositional signature in He-3-rich solar particle events”, G.M. Mason, D.V. 
Reames, T.T. von Rosenvinge, B. Klecker and D. Hovestadt, Ap.  J., 303, 849-860, (1986). 
[5]  “A comparison of solar helium-3-rich events with type II bursts and coronal mass ejections”, S. 
Kahler, D.V. Reames, N.R, Sheeley, Jr., R.A. Howard, D.J. Michels and M.J. Koomen, Ap. J., 290, 
742-747 (1985). 
[6]  “Two classes of solar energetic particle events associated with impulsive and long-duration soft X-
ray flares”, H.V. Cane, R.E. McGuire and T.T. von Rosenvinge, Ap. J., 301, 448-459 (1986). 
0.03
0.3
3
1 10
Fl
ux
 (n
eu
tr
on
s/
((M
eV
/n
uc
)‐s
‐cm
2 )
Energy (MeV)
lunar prospector
measurement
calculation
Figure 2: A comparison of the calculated lunar neutron albedo 
spectrum with spectrum measured on the Lunar Prospector 
Mission. 
 4
[7]   “Measurements of the Ionic Charge States of Solar Energetic Particles using the Geomagnetic 
Field”, R.A. Leske, J.R. Cummings, R.A. Mewaldt, and E.C. Stone, Ap.J. Letters, 452, L149-L152 
(1995). 
[8]  “Solar Energetic Fe Charge State Measurements: Implications for Acceleration by Coronal Mass 
Ejection-Driven Shocks”, P.R. Boberg, A.J. Tylka, and J.H. Adams, Jr., Ap.J. Letters, 471, L65-L68 
(1996). 
[9] “Rate Prediction for Single Event Effects – A Critique”, E.L. Petersen, J.C. Pickel, J.H. Adams, Jr. 
and E.C. Smith, IEEE TNS, 39, 1577-1599 (1992). 
[10] “CREME96: A Revision of the Cosmic Ray Effects on Micro-Electronics Code”, Allan J. Tylka, 
James H. Adams, Jr., Paul R. Boberg, Buddy Brownstein, William F. Dietrich, Erwin O. Flueckiger, 
Edward L. Petersen, Margaret A. Shea, Don F. Smart, and Edward C. Smith, IEEE TNS, 44, 2150-
2160 (1997). 
[11] “Cosmic-Ray-Induced Errors in MOS Devices” James C. Pickel and James T. Blandford, Jr., IEEE 
TNS, NS-27, 1006-1014 (1980). 
[12] “Space environment (natural and artificial) — Galactic cosmic ray model”, R.A. Nymmik, Intl. Stds. 
Org., ISO 15390, (2004). 
[13] “The CRRES/SPACERAD heavy ion model of the environment (CHIME) for cosmic ray and solar 
particle effects on electronic and biological systems in space”,  D.L. Chenette, J. Chen, E. Clayton, 
T.G. Guzik, J.P. Wefel, M. Garcia-Munoz, C. Lopate, K.R. Pyle, K.P. Ray, E.G. Mullen, D.A. 
Hardy, IEEE TNS., 41, 2332-2339 (1994). 
[14]  “Badhwar–O’Neill galactic cosmic ray model update based on advanced composition explorer 
(ACE) energy spectra from 1997 to present”, P.M., O’Neill, Adv. in Space Res., 37, 1727-1733 
(2006). 
[15]  “Badhwar–O'Neill 2010 Galactic Cosmic Ray Flux Model—Revised” P.M. O'Neill, 57, 3148 – 3153 
(2010). 
[16]  “UPROP A Heavy-ion Propagation Code”, Severn Communications Corporation, SCC Report, 89–
102, 1989. 
[17] “Comparisons of Several Transport Models in Their Predictions in Typical Space Radiation 
Environments”, Z.W. Lin, J.H. Adams, A.F. Barghouty, S.D. Randeniya, R.K. Tripathi, J.W. Watts 
and P.P. Yepes, Adv. Sp. Res., 49, 797–806 (2012). 
[18] “HZETRN: description of a free-space ion and nucleon transport and shielding computer program”, 
J.W. Wilson, F.F. Badavi, F.A. Cucinotta, J.L. Shinn, G.D. Badhwar, R. Silberberg, C.H. Tsao, L.W. 
Townsend and R.K. Tripathi, NASA Technical Paper 3495 (1995). 
[19]  “FLUKA code: description and benchmarking”, G. Battistoni, S. Muraro, P.R. Sala, F. Cerutti, A. 
Ferrari, S. Roesler, A. Fassò and J. Ranft, The. Proceedings of the Hadronic Shower Simulation 
Workshop 2006, Fermilab, 6-8 September 2006, M. Albrow, R. Raja eds., AIP Conference 
Proceeding 896, 31-49 (2007). 
[20]  “GEANT4 - a simulation toolkit”, S. Agostinelli, J. Allison, K. Amako, J. Apostolakis, H. Araujo, P. 
Arce, M. Asai, D. Axen, S. Banerjee and D. Zschiesche,. Nucl. Instr. Meth. A506, 250-303 (2003). 
[21] “The Trapped Proton Environment in Medium Earth Orbit (MEO)”, G.P. Ginet, S.L. Huston, C.J. 
Roth, T.P. O'Brien and T.B. Guild, IEEE TNS, 57, 3135-3142 (2010). 
[22] “A geomagnetic cutoff rigidity interpolation tool: Accuracy verification and application to space 
weather”, D.F. Smart, M.A. Shea, A.J. Tylka and P.R. Boberg, Adv. in Sp. Res. 37, 1206–1217 
(2006). 


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