Focus Topics and New Strategic Capabilities

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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

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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 Earths atmosphere
  nearing completion

http//emmrem.bu.edu
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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
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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 BCs 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
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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 BCs 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
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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)

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EMMREM Framework
Schwadron et al., Space Weather Journal, 2010
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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

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EPREM simulations
Kozarev et al., submitted to SWJ
Dayeh et al., submitted to SWJ
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Source reveals extremely broad longitudinal
distribution
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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.

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Doses exceed limits with spacesuit shielding,
below limits for spacecraft shielding
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Dose rate and dose at Martian atmospheric heights
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Radiation Exposure from Large SPE Events
BFO dose rate during Aug.. 1972 SPE Event
Cumulative dose
Myung-Hee et al., 2006
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Coupling to MHD
Coupling between EPREM and WSA/Enlil
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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
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Results of Physics-Based Simulated Event (PATH
Code)
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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

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EMMREM at CCMC
Delivered and installed EMMREM successfully.
More information about the model
at http//ccmc.gsfc.nasa.gov/models/modelinfo.ph
p?modelEMMREM
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Integrated Risk Projection
EMMREM
Space Radiation Environment
Mitigation - Shielding materials
Risk Assessment -Dosimetry -Biomarkers -Uncertain
ties -Space Validation
Radiation Shielding
Initial Cellular and Tissue Damage DNA breaks,
tissue microlesions
- Radioprotectants
DNA repair, Recombination, Cell cycle
checkpoint, Apoptosis, Mutation, Persistent
oxidative damage, Genomic Instability
-Pharmaceuticals
Tissue and Immune Responses
Riskj (age,sex,mission)
Risks Chronic Cancer, Cataracts, Central
Nervous System, Heart Disease Acute Lethality,
Sickness, Performance
Risks Acute Radiation Syndromes Cancer Cataracts
Neurological Disorders
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Major Questions for Acute Risk Models

• What are the dose-rate modification (DRM) effects
  for SPE Acute risks?
• What are the Relative Biological Effectieness
  (RBEs) for protons and secondaries?
• How do DRM and RBEs 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?

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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

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Probabilistic Solar Particle Flux Forecast
Modeling
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SPE Database for the Recent Solar Cycles
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Model-based Prediction of SPE Frequency based on
the Measurements of SPE Flux
Propensity of SPEs Hazard Function of Offset b
Distribution Density Function
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m1783rd day
Typical Nonspecific Future Cycle
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Approaches

• Cumulative frequency distribution of recorded
  SPEs
• 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 F30, 60, or 100 distribution for
  each mission periods by a random draw from Gamma
  distribution