The harmful effects of space radiation pose a serious health risk to astronauts participating in future long-term missions. Such radiation effects must be considered in the design phase of space vessels as well as in mission planning. Crew radioprotection during long periods in deep space (e.g., transit to Mars) represents a major challenge, especially because of the strong restrictions on the passive shielding load allowed on-board the vessel. Novel materials with better shielding performance compared to the “gold standard” high-density polyethylene are therefore greatly needed. Because of the high hydrogen content of hydrides, lithium hydride has been selected as a starting point for further studies of promising candidates to be used as passive shielding materials. In the current experimental campaign, the shielding performance of lithium hydride was assessed by measuring normalized dose, primary beam attenuation and neutron ambient dose equivalent using 430 MeV/u 12C, 600 MeV/u 12C and 228 MeV proton beams. The experimental data were then compared to predictions from the Monte Carlo transport codes PHITS and GRAS. The experimental results show an increased shielding effectiveness of lithium hydride compared to reference materials like polyethylene. For instance, the attenuation length for 600 MeV/u 12C primary particles in lithium hydride is approximately 20% shorter compared to polyethylene. Furthermore, the comparison results between both transport codes indicates that the standard Tripathi-based total reaction cross-section model of PHITS cannot accurately reproduce the presented experimental data, whereas GRAS shows reasonable agreement.
Experimental Assessment of Lithium Hydride's Space Radiation Shielding Performance and Monte Carlo Benchmarking
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Christoph Schuy, Chiara La Tessa, Felix Horst, Marta Rovituso, Marco Durante, Martina Giraudo, Luca Bocchini, Marcello Baricco, Alberto Castellero, Gianluca Fioreh, Uli Weber; Experimental Assessment of Lithium Hydride's Space Radiation Shielding Performance and Monte Carlo Benchmarking. Radiat Res 1 February 2019; 191 (2): 154–161. doi: https://doi.org/10.1667/RR15123.1
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