Focus Topics and New
Strategic Capabilities
N. A. Schwadron, K. Kozarev, L. Townsend, M. Desai,
M. A. Dayeh, F. Cucinotta, D. Hassler, H. Spence, M.
PourArsalan, K. Korreck, R. Squier, M. Golightly, G.
Zank, X. Ao, M. Kim, C. Zeitlin, G. Li, O.
Verkhoglyadova
Current Capabilities
• Acute time-dependent radiation environment near Earth,
Moon, Mars and throughout the inner heliosphere
• Linear-Energy-Spectra at the Moon (LET spectra
through the heliosphere underway)
• Testing/model validation via comparison to Ulysses,
CRaTER, Marie
• Radiation environment specified from energetic particle
simulations (e.g., PATH code and LFM-Helio coupling
underway)
• Radiation environment through Mars atmosphere
• Radiation environment through Earth’s atmosphere
nearing completion
http://emmrem.bu.edu
Module Availability
• Open source software available on request and
distributed through subversion
• Module Web Interface through the EMMREM
Website
• Module delivered and installed at the CCMC
– BRYNTRN radiation transport model running in real time
– Working on coupling between BRYNTRN and the ReleASE
model
• EMMREM delivered and up and running at the Space
Radiation Group (SRAG)
http://emmrem.bu.edu
Drivers, Boundary Conditions,
Model Integration
• Boundary conditions specified from observed energetic particle
fluxes and solar wind measurements from spacecraft at or
inside 1 AU (Helios, ACE, GOES, SOHO)
• Model Coupling
– MHD models (e.g., ENLIL, LFM-Helio) specify the plasma
environment through which energetic particle simulations run
• Energetic particle modules couple to ENLIL, which in turn has inner
BC’s from source surface models using synoptic maps and
photospheric magnetograms
• Coupling with Modeled CMEs (e.g., Cone Model CMEs via ENLIL)
– Radiation environment coupled with particle simulations (particle
simulation codes become drivers)
– Radiation environment from predictive models using energetic
particle precursors (e.g., coupling to the Release model)
http://emmrem.bu.edu
Future Capabilities Needed
• Probabilistic solar particle flux forecast modeling
• Coupling between EMMREM and integrated risk models for
comprehensive SPE scenario models
• Radiation environment from extreme events
– How bad can the environment be?
– How probable are extreme events?
– What is the physics behind extreme events?
• Further modeling of events with BC’s from inside 1 AU to validate
forecasting methods
– Messenger
– Events and coupling with Release model
– Future: Solar Orbiter, Solar Probe Plus
http://emmrem.bu.edu
Future - Physics of SEPs
• Determine Peak intensity and Fluence gradients inside 1 AU
• Role of CME shocks vs flares (e.g., determine coronal heights
where CMEs first drive SEP-producing shocks)
• CME shock acceleration efficiency (e.g., quasi-parallel vs quasiperp, preceding CMEs, seed particle variability)
• Generation and dissipation of self-excited waves and their effects on
streaming limits and rigidity-dependent spectral breaks
• Role of rigidity-dependent scattering and diffusion on particle fluxes
at 1 AU
• Multiple observational vantage points beyond 1 AU to determine
gradients, understand transport, and validate models (e.g., Cassini,
Mars missions, planetary probes)
EMMREM Framework
Schwadron et al., Space Weather Journal, 2010
7
EMMREM: Primary
Transport
•
•
•
•
•
Energetic Particle Radiation
Environment Module (EPREM)
Physical 3-D kinetic mode for
the transport of energetic
particles in a Lagrangian fieldaligned grid (Kota, 2005)
including pitch-angle scattering,
curvature and gradient drift,
perpendicular transport
Capable of simulating transport
of protons electrons and heavier
ions
Currently driven by data at 1 AU
(Goes, SOHO/ERNE)
Run on an event-by-event basis
EPREM simulations
Dayeh et al., submitted to SWJ Kozarev et al., submitted9 to
SWJ
Source reveals extremely broad longitudinal distribution
EMMREM:
Secondary Transport
 Radiation transport – Input is time series from EPREM.
- BRYNTRN (BaRYoN TraNsport) code for light ions, primarily for SEP calculations;
- HZETRN code for high Z primary and secondary ions transport – for SEP and
GCR calculations; Look-up tables for Mars atmosphere.
- HETC-HEDS (High-Energy Transport Code – Human Exploration and
Development of Space) Monte Carlo code; Look-up tables for Earth atmosphere
 Scenarios
- Earth
- Moon
- Mars
- Interplanetary
Completed EMMREM framework capable of performing radiation
calculations that account for time-dependent positions, spacecraft
and human geometry, spacesuit shielding, atmospheres and
11 surface habitats.
Doses exceed limits with spacesuit shielding,
below limits for spacecraft shielding
Dose rate and dose at Martian
atmospheric heights
Radiation Exposure from Large SPE
Events
BFO dose
rate during
Aug.. 1972
SPE Event
Cumulative
dose
Myung-Hee et al., 2006
Coupling to MHD
Coupling between EPREM and WSA/Enlil
15
Coupling to MHD
Testing coupling to WSA/Enlil runs with cone model
 Coupling to a new MHD code being developed at BU (LFM-helio) underway

Kozarev et al., submitted to SWJ
16
Results of Physics-Based
Simulated Event (PATH Code)
EMMREM Web interface

Currently available:
- GOES proton input
- EPREM runs on request
- BRYNTRN runs on request
- Sim results visualization
• New functionality soon:
- Mars radiation environment
- LET specra for comparison with
CraTER
- Earth atmospheric radiation
environment
- Catalogue of historical events
with radiation environment
information
18
EMMREM at CCMC
Delivered and installed
EMMREM successfully.
More information about the model at:
http://ccmc.gsfc.nasa.gov/models/modelinfo.php?model
19
=EMMREM
Integrated Risk Projection
EMMREM
Space Radiation Environment
Mitigation:
- Shielding materials
- Radioprotectants
Radiation Shielding
Initial Cellular and Tissue Damage
Risk Assessment:
-Dosimetry
-Biomarkers
-Uncertainties
-Space Validation
DNA breaks, tissue microlesions
DNA repair, Recombination,
Cell cycle checkpoint, Apoptosis, Mutation,
Persistent oxidative damage, & Genomic Instability
-Pharmaceuticals
Tissue and Immune Responses
Risks:
Risks:Cataracts,
Chronic: Cancer,
Acute
Radiation
Central
NervousSyndromes
System,
Cancer
Heart Disease
Cataracts
Acute: Lethality,
Sickness,
Neurological
Disorders
Performance
Riskj
(age,sex,mission)
Major Questions for Acute Risk
Models
• What are the dose-rate modification (DRM) effects for
SPE Acute risks?
• What are the Relative Biological Effectieness (RBE’s) for
protons and secondaries?
• How do DRM and RBE’s vary with Acute risks?
• Are there synergistic effects from other flight stressors
(microgravity, stress, bone loss) or GCR on Acute risks?
• For which Acute risks are countermeasures needed?
• How can the effectiveness of Acute countermeasures be
evaluated and extrapolated to Humans?
Acute Radiation Risks
Research
• Overall Objectives
– Accurate Risk assessment models support
• Permissible Exposure Limits (PEL) Determination
• Informed Consent Process
• Operational Procedures
– Dosimetry
– EVA timelines
– Solar Forecasting Requirements
• Shielding Requirements
• Countermeasure (CM) Requirements
• Approach
– Probabilistic Risk Assessment applied to Solar Particle Events
(SPE)
– Models of acute risks used to evaluate acute CMs for SPE and
Lunar Surface conditions
– EMMREM provides a tool to evaluate and assess acute risks
Probabilistic Solar Particle Flux
Forecast Modeling
Date
20
05
20
02
19
99
22
2/
1/
2/
1/
2/
1/
19
96
19
93
19
90
19
87
21
2/
1/
2/
1/
2/
1/
2/
1/
1.E+07
1.E+10
2/
1/
1
2 / 9 54
1/
1
2 / 9 56
1/
1
2 / 9 58
1/
1
2 / 9 60
1/
1
2 / 9 62
1/
1
2 / 9 64
1/
1
2 / 9 66
1/
1
2 / 9 68
1/
1
2 / 9 70
1/
1
2 / 9 72
1/
1
2 / 9 74
1/
1
2 / 9 76
1/
1
2 / 9 78
1/
1
2 / 9 80
1/
1
2 / 9 82
1/
1
2 / 9 84
1/
1
2 / 9 86
1/
1
2 / 9 88
1/
1
2 / 9 90
1/
1
2 / 9 92
1/
1
2 / 9 94
1/
1
2 / 9 96
1/
1
2 / 9 98
1/
2
2 / 0 00
1/
2
2 / 0 02
1/
2
2 / 0 04
1/
20
06
20
19
84
19
81
19
78
1.E+09
2/
1/
2/
1/
2/
1/
19
75
19
72
19
69
19
66
19
63
19
60
19
57
19
54
-2
protons cm
19
2/
1/
2/
1/
2/
1/
2/
1/
2/
1/
2/
1/
2/
1/
2/
1/
100,

1.E+10
2/
1/
19
54
2/
1/
19
57
2/
1/
19
60
2/
1/
19
63
2/
1/
19
66
2/
1/
19
69
2/
1/
19
72
2/
1/
19
75
2/
1/
19
78
2/
1/
19
81
2/
1/
19
84
2/
1/
19
87
2/
1/
19
90
2/
1/
19
93
2/
1/
19
96
2/
1/
19
99
2/
1/
20
02
2/
1/
20
05
60, protons cm -2
 , protons cm
30
-2
SPE Database for the Recent Solar Cycles
1.E+11
SPE onset date
1.E+10
1.E+09
1.E+08
1.E+07
1.E+09
Date
1.E+08
23
Date
1.E+08
1.E+07
Model-based Prediction of SPE Frequency
based on the Measurements of SPE Flux
l
l
Propensity of SPEs: Hazard Function of Offset b Distribution Density Function
p

1
q

1
K

(
p

q
)
t
t




0
(
t
)


1

(
0

t

40
)
0



for
40
40

(
p
)

(
q
)
00
40
00
40
00
00




19
20
21
22
23
0.04
160
0.035
140
0.03
120
160
140
120
m=1783rd day
0.025
100
0.02
80
0.015
60
0.01
40
0.005
20
80
60
40
20
0
0
2/1/54
0
0
2/1/58
2/1/62
2/1/66
2/1/70
2/1/74
2/1/78
2/1/82
Date
2/1/86
2/1/90
2/1/94
2/1/98
2/1/02
2/1/06
500
1000
1500
2000
2500
3000
Elapsed time, d
Typical Nonspecific Future Cycle
3500
4000
l(t)
l (t)
100
Approaches
1. Cumulative frequency distribution of recorded SPEs
2. Model for the realistic application and the dependence
of multiple SPEs:
 Non-constant hazard function defined for the best
propensity of SPE data in space era
 Non-homogenous Poisson process model for SPE
frequency in an arbitrary mission period
 Cumulative probability of SPE occurrence during a
given mission period using fitted Poisson model
3. Simulation of 30, 60, or 100 distribution for each mission
periods by a random draw from Gamma distribution