logo The Earth-Moon-Mars Radiation Exposure Module

What is EMMREM?

As we prepare to return humans to the Moon and envision exploration to Mars and beyond, the need for a way to successfully mitigate the dangers of radiation exposure is swelling. Space radiation hazards pose one of the most serious issues to future human and robotic missions beyond Low-Earth Orbit, where bombardment from Galactic Cosmic Rays (GCRs) and Solar Energetic Particle events (SEP events) is a constant threat. For more about relevant radiation hazards, click here. The Earth-Moon-Mars Radiation Environment Module (EMMREM) provides a tool to describe time-dependent radiation exposure in the Earth-Moon-Mars and Interplanetary space environments. The numerical module integrates numerous sub-routines that describe radiation transport and planetary interactions, yielding predictions of exposure. It will be available for broad use by researchers and modelers, who can input almost any incident particle distribution from interplanetary space, and then observe the corresponding time-dependent dose-related quantities and Linear Energy Transfer (LET) spectra.

About the Module

EMMREM has been developed using contemporary state-of-the-art particle radiation models, designed with well-established, working codes, including the BRYNTRYN and HZETRN code developed at NASA and the HETC-HEDS Monte Carlo code developed at Oak Ridge National Laboratory and the University of Tennessee. Beyond this, it has the capability to incorporate new and improving models as they become available, yielding more accurate estimates of radiation hazards and effects. Moreover, it is constantly validated to significantly reduce uncertainties in predictions, using previous measurements from the International Space Station (ISS) and the Space Shuttle; LET spectra observed by LRO/CRaTER for Lunar scenarios; observations from MSL/RAD and MARIE on Odyssey for Mars scenarios; and an extensive data-base of Accelerator Beam Measurements. Direct observations of particle radiation (SOHO, ACE, Wind, STEREO, SAMPEX, NOAA-GOES and Ulysses) and selected simulations are used as input to predict radiation exposure. The 3-D observations by STEREO will be used to fully characterize and predict radiation exposure in events contemporaneously observed at the Moon and Mars by LRO/CRaTER and MSL/RAD. Observations and simulations will be studied to describe the extremes, statistics, and time variations of radiation exposure caused by SEPs and CRs.

Click here to read more about the EMMREM framework.

The results of EMMREM will improve risk assessment models, enabling adequate planning of future missions.


Mission Statement

The central objective of this project is to develop and validate a numerical module for completely characterizing time-dependent radiation exposure in the Earth-Moon-Mars and Interplanetary space environments. Given the energy spectrum, angular distribution, and elemental composition of particle radiation in the solar wind, it will provide the ability to predict radiation exposure anywhere on the surface of Earth, the Moon, or Mars, in Earth's Atmosphere, and in the space between Earth and Mars. The final product includes well-tested and straightforward interfaces for use by the public and scientific community.

What will this website provide?

The web-page provides links for users to choose specific simulated events and time-series, observed events and time-series, or user-specified input for the energy and angular distributions incident from interplanetary space. Users specify: (1) LEO, Moon, and Mars scenarios including altitudes and/or orbits and (2) shielding materials. The option to specify spacecraft, habitat, spacesuit, human CAF/CAM models, and surface (albedo) effects will be available in the future. Module outputs are retrievable as time-series and time-averages. These may be compared to observed events (LRO/CRaTER, MSL/RAD, MARIE, ISS, Space Shuttle) or accelerator measurement case studies.

To request access to the website or more information about the project, click here.


This material is based upon work supported by the National Science Foundation under Grant No. NNX07AC14G.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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