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Focus Topics and New Strategic Capabilities

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.

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Focus Topics and New Strategic Capabilities

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  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  8. 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

  10. 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.

  12. Doses exceed limits with spacesuit shielding, below limits for spacecraft shielding

  13. Dose rate and dose at Martian atmospheric heights

  14. 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. 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

  17. 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

  20. Integrated Risk Projection EMMREM Space Radiation Environment Mitigation: - Shielding materials Risk Assessment: -Dosimetry -Biomarkers -Uncertainties -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

  21. 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?

  22. 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

  23. Probabilistic Solar Particle Flux Forecast Modeling

  24. SPE Database for the Recent Solar Cycles 19 20 21 22 23

  25. Model-based Prediction of SPE Frequency based on the Measurements of SPE Flux Propensity of SPEs: Hazard Function of Offset b Distribution Density Function 19 20 21 22 23 m=1783rd day Typical Nonspecific Future Cycle

  26. Approaches • Cumulative frequency distribution of recorded SPEs • Model for the realistic application and the dependence • of multipleSPEs: • 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

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