Galactic cosmic ray environment predictions for the NASA BioSentinel mission

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-08-01 DOI:10.1016/j.lssr.2023.05.001
S. Rahmanian , T.C. Slaba , L.A. Braby , S.R. Santa Maria , S. Bhattacharya , T. Straume
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引用次数: 1

Abstract

BioSentinel is a nanosatellite deployed from Artemis-I designed to conduct in-situ biological measurements on yeast cells in the deep space radiation environment. Along with the primary goal of measuring damage and response in cells exposed during spaceflight, on-board active dosimetry will provide measurements of the radiation field encountered behind moderate shielding provided by the BioSentinel housing and internal components. The measurements are particularly important to enable interpretation of biological observations but also provide an opportunity to validate integrated computational models used to calculate radiation environments. In this work, models are used to predict the galactic cosmic ray exposure anticipated for the BioSentinel payload and on-board dosimeter. The model calculations presented herein were completed prior to the Artemis-I launch on November 16, 2022, and therefore represent actual predictions (i.e., unbiased by a priori knowledge of on-board measurements). Such time-forward predictions are rarely performed for space radiation applications due to limitations of environmental models, but truly independent model validation will be possible in the future when on-board measurements become available. The method used to facilitate future projections within an existing GCR (galactic cosmic ray) environmental model is described, and projection uncertainties are quantified and contextualized.

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美国国家航空航天局生物哨兵任务的银河宇宙射线环境预测。
BioSentinel是Artemis-I部署的一颗纳米卫星,旨在对深空辐射环境中的酵母细胞进行原位生物测量。除了测量太空飞行过程中暴露的细胞的损伤和反应的主要目标外,机载主动剂量测定还将提供对BioSentinel外壳和内部组件提供的中等屏蔽后遇到的辐射场的测量。这些测量对于解释生物观测结果尤其重要,但也为验证用于计算辐射环境的集成计算模型提供了机会。在这项工作中,模型用于预测BioSentinel有效载荷和机载剂量计预计的银河系宇宙射线暴露。本文提供的模型计算是在2022年11月16日Artemis-I发射之前完成的,因此代表了实际预测(即,通过机载测量的先验知识无偏)。由于环境模型的限制,这种时间前向预测很少用于空间辐射应用,但未来当机载测量可用时,真正独立的模型验证将是可能的。描述了在现有的GCR(银河宇宙线)环境模型中用于促进未来预测的方法,并对预测的不确定性进行了量化和情境化。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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