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Radiation protection for interplanetary manned missions

Radiation protection for interplanetary manned missions. S. Guatelli 1 , B. Mascialino 1 , P. Nieminen 2 , M. G. Pia 1 INFN, Genova, Italy ESA-ESTEC, Noordwijk, The Netherlands . Monte Carlo 2005 18-21 April 2005. www.ge.infn.it/geant4/space/remsim. Context.

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Radiation protection for interplanetary manned missions

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  1. Radiation protection for interplanetary manned missions • S. Guatelli1, B. Mascialino1, P. Nieminen2, M. G. Pia1 • INFN, Genova, Italy • ESA-ESTEC, Noordwijk, The Netherlands Monte Carlo 2005 18-21 April 2005 www.ge.infn.it/geant4/space/remsim

  2. Context • Planetary exploration has grown into a major player in the vision of space science organizations like ESA and NASA • The study of the effects of space radiation on astronauts is an important concern of missions for the human exploration of the solar system • The radiation hazard can be limited: • selecting traveling periods and trajectories • providing adequate shielding in the transport vehicles and surface habitats

  3. The ESA REMSIM project • A project in the European AURORA programme • Protection of the crew from the interplanetary space radiation • Space radiation monitoring • Design of the crew habitats • Trajectories from the Earth to Mars to limit the exposure of astronauts to harmful effects of radiation • Transfer vehicles • compare the shielding properties of an inflatable habitat w.r.t. a conventional rigid structure • materials and thicknesses of shielding structures • Habitats on a planetary surface • using local resources as building material • Radiation environment

  4. The REMSIM Simulation Project A project in the framework of the AURORA programme of the European Space Agency Vision A firstquantitative analysis of the shielding properties of some conceptual designs of vehicle and surface habitats Comparison among different shielding options

  5. Software strategy • Object oriented technology • suitable to long term studies • openness of the software to extensions and evolution • it facilitates the maintainability of the software over a long time scale • Geant4 as Simulation Toolkit • open source, general purpose Monte Carlo code for particle transport based on OO technology • versatile to describe geometries and materials • rich set of physics models • The data analysis is based on AIDA • abstract interfaces make the software system independent from any concrete analysis tools • strategy meaningful for a long term project, subject to the future evolution of software tools

  6. Software process • Quality and reliability of the software are essential requirements for a critical domain like radioprotection in space • Iterative and incremental process model • Develop, extend and refine the software in a series of steps • Get a product with a concrete value and produce results at each step • Assess quality at each step • Rational Unified Process (RUP) adopted as process framework • Mapped onto ISO 15504 adopt a rigorous software process Talk: Experience with software process in physics projects, 18 April, Monte Carlo 2005

  7. Summary of process products http://www.ge.infn.it/geant4/space/remsim/environment/artifacts.html

  8. Architecture Driven by goals deriving from the Vision • Design an agilesystem • capable of providing first indications for the evaluation of vehicle concepts and surface habitat configurations within a short time scale • Design an extensible system • capable of evolution for further more refined studies, without requiring changes to the kernel architecture • Documented in the Software Architecture Document http://www.ge.infn.it/geant4/space/remsim/design/SAD_remsim.html

  9. REMSIM Simulation Design

  10. Vehicle concepts Surface habitats Astronaut Electromagnetic processes + Hadronic processes Strategy of the Simulation Study • Model the radiation spectrum according to current standards • Simplified angular distribution to produce statistically meaningful results • Physics modeled by Geant4 • Select appropriate models from the Toolkit • Verify the accuracy of the physics models • Distinguish e.m. and hadronic contributions to the dose • Simplified geometrical configurations • retaining the essential characteristics for dosimetry studies • Evaluate energy deposit/dose in shielding configurations • various shielding materials and thicknesses

  11. Space radiation environment • Galactic Cosmic Rays • Protons, α particles and heavy ions (C -12, O -16, Si - 28, Fe - 52) • Solar Particle Events • Protons and α particles 100K primary particles, for each particle type Energy spectrum as in GCR/SPE Scaled according to fluxes for dose calculation GCR: p, α, heavy ions SPE particles: p and α at 1 AU at 1 AU Envelope of CREME96 1977 and CREME86 1975 solar minimum spectra Envelope of CREME96 October 1989 and August 1972 spectra Worst case assumption for a conservative evaluation

  12. SIH - Simplified Inflatable Habitat Vehicle concepts Two (simplified) options of vehicles studied Simplified Rigid Habitat A layer of Al (structure element of the ISS) A multilayer structure consisting of: • MLI: external thermal protection blanket - Betacloth and Mylar • Meteoroid and debris protection - Nextel (bullet proof material) and open cell foam • Structural layer - Kevlar • Rebundant bladder - Polyethylene, polyacrylate, EVOH, kevlar, nomex Materials and thicknesses by ALENIA SPAZIO The Geant4 geometry model retains the essential characteristics of the vehicle concept relevant to a dosimetry study

  13. Sketch and sizes by ALENIA SPAZIO Surface Habitats • Example: surface habitat • Cavity in the moon soil + covering heap • Use of local material The Geant4 model retains the essential characteristics of the surface habitat concept relevant to a dosimetric study

  14. 30 cm Z Astronaut Phantom • The Astronaut is approximated as a phantom • a waterbox, sliced into voxels along the axis perpendicular to the incident particles • the transversal size of the phantom is optimized to contain the shower generated by the interacting particles • the longitudinal size of the phantom is a “realistic” human body thickness • The phantom is the volume where the energy deposit is collected • The energy deposit is given by the primary particles and all the secondaries created

  15. Selection of Geant4 EM Physics Models • Geant4 Low Energy Package for p, α, ions and their secondaries • Geant4 Standard Package for positrons • Verification of the Geant4 e.m. physics processes with respect to protocol data (NIST reference data, ICRU Report 49) • “Comparison of Geant4 electromagnetic physics models against the NIST reference data”, submitted to IEEE Trans. Nucl. Sci. The electromagnetic physics models chosen are accurate Compatible with NIST data within NIST accuracy (p-value > 0.9) Talk: Precision Validation of Geant4 electromagnetic physics, 20 April, Monte Carlo 2005

  16. Geant4 hadronic physics • Complementary and alternative models • Parameterised, data driven and theory driven models • The most complete hadronic simulation kit available on the market • Models for p and α • Hadronic models for ions in progress Intrinsic complexity of hadronic physics Geant4 hadronic physics is still the object of validation studies The dosimetry studies performed in REMSIM must be considered as a first indication of the hadronic contribution rather than as a quantitative estimate

  17. Selection of Geant4 Hadronic Physics Models + hadronic elastic process

  18. vacuum air e.m. physics e.m. + Bertini set e.m. + Binary set GCR Adding the hadronic interactions on top of the e.m. interactions increase the energy deposit in the phantom by ~ 25 % 10 cm water shielding phantom multilayer - SIH Electromagnetic and hadronic interactions 100 k events GCR p 100 k events e.m. physics e.m. + Binary ion set GCR α The contribution of the hadronic interactions looks negligible in the calculation of the energy deposit

  19. vacuum air GCR water / poly shielding phantom multilayer - SIH Shielding materials • Water • Polyethylene • Equivalent shielding results 100 k events GCR p e.m. physics + Bertini set e.m. physics only 10 cm water 10 cm polyethylene

  20. vacuum air GCR 5 / 10 cm water shielding phantom multilayer - SIH Shielding thickness 100 k events e.m. physics+ Bertini set GCR p 10 cm water 5 cm water GCR α e.m. physics+ hadronic physics 10 cm water 5 cm water Doubling the shielding thickness decreases the energy deposit by ~10% 100 k events Doubling the shielding thickness decreases the energy deposit ~ 15%

  21. vacuum air GCR 2.15 cm Al 5 cm water phantom 10 cm water 4 cm Al Al structure Comparison of inflatable and rigid habitat concepts • Aluminum layer replacing the inflatable habitat • based on similar structures as in the ISS • Two hypotheses of Al thickness • 4 cm Al • 2.15 cm Al • The shielding performance of the inflatable habitat is equivalent to conventional solutions 100 k events GCR p

  22. α vacuum air O-16 C-12 GCR Fe-52 Si-28 10 cm water shielding phantom multilayer - SIH Effects of cosmic ray components Protons e.m. physics processes only Relative contribution to the equivalent dose from some cosmic rays components 100 k events The dose contributions from proton and α GCR components result significantly larger than for other ions

  23. GCR p E> 30 GeV 8 % vacuum air GCR 10 cm water shielding phantom multilayer - SIH High energy cosmic ray tail 100 k events • The relative contribution from hadronic interactions w.r.t. electromagnetic ones increases at higher cosmic ray energies BUT • The high energy component represents a small fraction of the cosmic ray spectrum e.m. physics + Bertini set e.m. physics only Energy deposit GCR protons E > 30 GeV

  24. shielding vacuum air Incident radiation SPE shelter phantom multilayer shielding SIH SPE shelter model • Inflatable habitat • + additional 10 cm water shielding • + 70 cm water SPE shelter Shelter Geant4 model

  25. SPE p SPE α SPE E > 300 MeV / nucl e.m. + hadronic physics – Bertini set SPE, Inflatable habitat + shielding + shelter SPE energy deposit (MeV) vs depth (cm) e.m. + hadronic physics The SPE α contribution is weighted according to the spectrum with respect to protons • 100 K events: • 4 protons reach the astronaut • All α particles are stopped Study the energy deposit of SPE with E > 300 MeV/nucl

  26. x = 0 - 3 m roof thickness Add a log on top with variable height x vacuum moon soil GCR SPE beam x Phantom Moon surface habitats The moon as an intermediate step in the exploration of Mars 4 cm Al 4 cm Al GCR p GCR α e.m. + hadronic physics (Bertini set) 100 k events Energy deposit in the phantom vs. roof thickness

  27. SPE p – 0.5 m roof SPE α– 0.5 m roof SPE p – 3.5 m thick roof Planetary surface habitats – Moon - SPE • Energy deposit resulting from SPE with E > 300 MeV / nucl • The energy deposit of SPE a is weighted according to the flux with respect to SPE protons • The roof limits the exposure to SPE particles e.m. + hadronic physics (Bertini set) SPE α – 3.5 m thick roof 100 k events Energy deposit in the phantom given by Solar Particle protons and α particles

  28. Comments on the results • Simplified Inflatable Habitat + shielding • water / polyethylene are equivalent as shielding material • optimisation of shielding thickness is needed • hadronic interactions are significant • an additional shielding layer, enclosing a special shelter zone, is effective against SPE • The shielding properties of an inflatable habitat are comparable to the ones of a conventional aluminum structure • Moon Habitat • thick soil roof limits GCR and SPE exposure • its shielding capabilities against GCR are better than conventional Al structures similar to ISS

  29. Conclusions • The REMSIM project represents the first attempt in the European AURORA programme to estimate the radiation protection of astronauts quantitatively • REMSIM has demonstrated the feasibility of rigorous simulation studies for interplanetary manned missions, based on modern software tools and technologies • The advanced software technologies adopted make the REMSIM simulation suitable to future extensions and evolution for more detailed radiation protection studies • More details in a paper on Geant4 REMSIM Simulation in preparation • Thanks to all REMSIM team members for their collaboration • in particular to V. Guarnieri, C. Lobascio, P. Parodi and R. Rampini

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