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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 quasi-
perp, 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)
7
EMMREM Framework
Schwadron et al., Space Weather Journal, 2010
EMMREM: Primary Transport
• Energetic Particle Radiation Environment Module (EPREM)
• Physical 3-D kinetic mode for the transport of energetic particles in a Lagrangian field-aligned 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
9
EPREM simulations
Kozarev et al., submitted to SWJ
Dayeh et al., submitted to SWJ
Source reveals extremely broad longitudinal distribution
11
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 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
15
Coupling to MHD
Coupling between EPREM and WSA/Enlil
16
Kozarev et al., submitted to SWJ
Testing coupling to WSA/Enlil runs with cone model Coupling to a new MHD code being developed at BU (LFM-helio) underway
Coupling to MHD
Results of Physics-Based Simulated Event (PATH Code)
18
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
19
EMMREM at CCMC
Delivered and installed EMMREM successfully.
More information about the model at:
http://ccmc.gsfc.nasa.gov/models/modelinfo.php?model=EMMREM
Space Radiation Environment
Integrated Risk ProjectionIntegrated Risk Projection
Radiation Shielding
Initial Cellular and Tissue DamageDNA breaks, tissue microlesions
DNA repair, Recombination, Cell cycle checkpoint, Apoptosis, Mutation,
Persistent oxidative damage, & Genomic Instability
Tissue and Immune Responses
Risks:Acute Radiation Syndromes
CancerCataracts
Neurological Disorders
Mitigation:
- Shielding materials
- Radioprotectants
-Pharmaceuticals
Riskj
(age,sex,mission)
Risk Assessment:-Dosimetry-Biomarkers-Uncertainties-Space Validation
Risks:Chronic: Cancer, Cataracts,
Central Nervous System, Heart Disease
Acute: Lethality, Sickness, Performance
EMMREM
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
1.E+07
1.E+08
1.E+09
1.E+10
2/1/19542/1/19562/1/19582/1/19602/1/19622/1/19642/1/19662/1/19682/1/19702/1/19722/1/19742/1/19762/1/19782/1/19802/1/19822/1/19842/1/19862/1/19882/1/19902/1/19922/1/19942/1/19962/1/19982/1/20002/1/20022/1/20042/1/2006
Φ60, protons cm
-2
1.E+07
1.E+08
1.E+09
1.E+10
2/1/19542/1/19572/1/19602/1/19632/1/19662/1/19692/1/19722/1/19752/1/19782/1/19812/1/19842/1/19872/1/19902/1/19932/1/19962/1/19992/1/20022/1/2005
Φ100
, protons cm
-2
1.E+07
1.E+08
1.E+09
1.E+10
1.E+11SPE onset date
19 20 21 22 23
SPE Database for the Recent Solar Cycles
0
20
40
60
80
100
120
140
160
2/1/54 2/1/58 2/1/62 2/1/66 2/1/70 2/1/74 2/1/78 2/1/82 2/1/86 2/1/90 2/1/94 2/1/98 2/1/02 2/1/06
Date
λ( )t
Propensity of SPEs: Hazard Function of Offset Distribution Density Function
)40000(for4000
14000)()(
)(
40004000)(
110 ≤≤⎟
⎠
⎞⎜⎝
⎛ −⎟⎠
⎞⎜⎝
⎛ΓΓ+Γ
+=−−
ttt
qpqpK
tqpλλ
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0 500 1000 1500 2000 2500 3000 3500 4000
Elapsed time, d
0
20
40
60
80
100
120
140
160
λ( )t
=1783rd day
Typical Nonspecific Future Cycle
19 20 21 22 23
Model-based Prediction of SPE Frequency based on the Measurements of SPE Flux
Approaches
1. Cumulative frequency distribution of recorded SPEs2. Model for the realistic application and the dependence of multiple SPEs:
1. Non-constant hazard function defined for the best propensity of SPE data in space era
2. Non-homogenous Poisson process model for SPE frequency in an arbitrary mission period
3. Cumulative probability of SPE occurrence during a given mission period using fitted Poisson model
3. Simulation of Φ30, 60, or 100 distribution for each mission periods by a random draw from Gamma distribution
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